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Parallel computational optimization in operations research: a new integrative framework, literature review and research directions. (English) Zbl 1443.90002
Summary: Solving optimization problems with parallel algorithms has a long tradition in OR. Its future relevance for solving hard optimization problems in many fields, including finance, logistics, production and design, is leveraged through the increasing availability of powerful computing capabilities. Acknowledging the existence of several literature reviews on parallel optimization, we did not find reviews that cover the most recent literature on the parallelization of both exact and (meta)heuristic methods. However, in the past decade substantial advancements in parallel computing capabilities have been achieved and used by OR scholars so that an overview of modern parallel optimization in OR that accounts for these advancements is beneficial. Another issue from previous reviews results from their adoption of different foci so that concepts used to describe and structure prior literature differ. This heterogeneity is accompanied by a lack of unifying frameworks for parallel optimization across methodologies, application fields and problems, and it has finally led to an overall fragmented picture of what has been achieved and still needs to be done in parallel optimization in OR. This review addresses the aforementioned issues with three contributions: First, we suggest a new integrative framework of parallel computational optimization across optimization problems, algorithms and application domains. The framework integrates the perspectives of algorithmic design and computational implementation of parallel optimization. Second, we apply the framework to synthesize prior research on parallel optimization in OR, focusing on computational studies published in the period 2008–2017. Finally, we suggest research directions for parallel optimization in OR.
Reviewer: Reviewer (Berlin)
MSC:
90-08 Computational methods for problems pertaining to operations research and mathematical programming
65Y05 Parallel numerical computation
90C59 Approximation methods and heuristics in mathematical programming
90-02 Research exposition (monographs, survey articles) pertaining to operations research and mathematical programming
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[1] Abbasian, R.; Mouhoub, M., A hierarchical parallel genetic approach for the graph coloring problem, Applied Intelligence, 39, 3, 510-528 (2013)
[2] Abouelfarag, A. A.; Aly, W. M.; Elbialy, A. G., Performance analysis and tuning for parallelization of ant colony optimization by using OpenMP, Proceedings of the 14th IFIP tc 8 international conference on computer information systems and industrial management, 73-85 (2015)
[3] Abu-lebdeh, G.; Chen, H.; Ghanim, M., Improving performance of genetic algorithms for transportation systems: case of parallel genetic algorithms, Journal of Infrastructure Systems, 22, 4 (2016)
[4] Adamidis, P., Review of parallel genetic algorithms bibliography, Aristotle University of Thessaloniki, Thessaloniki, Greece, Technical Report (1994)
[5] Adel, D.; Bendjoudi, A.; El-Baz, D.; AitZai, A., GPU-based two level parallel B&B for the blocking job shop scheduling problem, IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Chicago, IL, USA, 747-755 (2016)
[6] Agrawal, J.; Mathew, T. V., Transit route network design using parallel genetic algorithm, Journal of Computing in Civil Engineering, 18, 3, 248-256 (2004)
[7] Aitzai, A.; Boudhar, M., Parallel branch-and-bound and parallel PSO algorithms for job shop scheduling problem with blocking, International Journal of Operational Research, 16, 1, 14-37 (2013) · Zbl 1362.90180
[8] Alba, E., Parallel metaheuristics: A new class of algorithms, 47 (2005), John Wiley & Sons · Zbl 1094.90052
[9] Alba, E.; Luque, G., Measuring the performance of parallel metaheuristics chapter 2,, 43-62 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey · Zbl 1278.90456
[10] Alba, E.; Luque, G.; Nesmachnow, S., Parallel metaheuristics: recent advances and new trends, International Transactions in Operational Research, 20, 1, 1-48 (2013) · Zbl 1263.90129
[11] Alba, E.; Talbi, E.-G.; Luque, G.; Melab, N., Metaheuristics and parallelism chapter 4,, 79-103 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey · Zbl 1278.90455
[12] Alba, E.; Tomassini, M., Parallelism and evolutionary algorithms, IEEE Transactions on Evolutionary Computation, 6, 5, 443-462 (2002)
[13] Alba, E.; Troya, J. M., A survey of parallel distributed genetic algorithms, Complexity, 4, 4, 31-52 (1999)
[14] Aldasoro, U.; Escudero, L. F.; Merino, M.; Monge, J. F.; Perez, G., On parallelization of a stochastic dynamic programming algorithm for solving large-scale mixed 0-1 problems under uncertainty, Top, 23, 3, 703-742 (2015) · Zbl 1327.90146
[15] Aldasoro, U.; Escudero, L. F.; Merino, M.; Perez, G., A parallel branch-and-fix coordination based matheuristic algorithm for solving large sized multistage stochastic mixed 0-1 problems, European Journal of Operational Research, 258, 2, 590-606 (2017) · Zbl 1394.90443
[16] Aldinucci, M.; Campa, S.; Danelutto, M.; Kilpatrick, P.; Torquati, M., Pool evolution: a parallel pattern for evolutionary and symbolic computing, International Journal of Parallel Programming, 44, 3, SI, 531-551 (2016)
[17] Almeida, F.; Gonzlez, D.; Pelez, I., Parallel dynamic programming chapter 2,, 29-51 (2006), John Wiley & Sons, Inc., Hoboken, New Jersey
[18] Arellano-Verdejo, J.; Godoy-Calderon, S.; Alonso-Pecina, F.; Guzman Arenas, A.; Antonio Cruz-Chavez, M., A new efficient entropy population-merging parallel model for evolutionary algorithms, International Journal of Computational Intelligence Systems, 10, 1, 1186-1197 (2017)
[19] Arrondo, A. G.; Redondo, J. L.; Fernandez, J.; Ortigosa, P. M., Solving a leader-follower facility problem via parallel evolutionary approaches, Journal of Supercomputing, 70, 2, 600-611 (2014)
[20] Aydin, M. E.; Sevkli, M., Sequential and parallel variable neighborhood search algorithms for job shop scheduling, Metaheuristics for scheduling in industrial and manufacturing applications, 125-144 (2008), Springer · Zbl 1151.90391
[21] Aydin, M. E.; Yigit, V., Parallel simulated annealing chapter 12,, 267-287 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey · Zbl 1137.90728
[22] Bak, S.; Blazewicz, J.; Pawlak, G.; Plaza, M.; Burke, E. K.; Kendall, G., A parallel branch-and-bound approach to the rectangular guillotine strip cutting problem, INFORMS Journal on Computing, 23, 1, 15-25 (2011) · Zbl 1243.90184
[23] Baños, R.; Ortega, J.; Gil, C., Hybrid MPI/OpenMP parallel evolutionary algorithms for vehicle routing problems, Proceedings of the 18th international conference on the applications of evolutionary computation, 653-664 (2014), Springer-Verlag Berlin
[24] Banos, R.; Ortega, J.; Gil, C.; De Toro, F.; Montoya, M. G., Analysis of OpenMP and MPI implementations of meta-heuristics for vehicle routing problems, Applied Soft Computing, 43, 262-275 (2016)
[25] Banos, R.; Ortega, J.; Gil, C.; Fernandez, A.; De Toro, F., A simulated annealing-based parallel multi-objective approach to vehicle routing problems with time windows, Expert Systems with Applications, 40, 5, 1696-1707 (2013)
[26] Barr, R. S.; Hickman, B. L., Reporting computational experiments with parallel algorithms: Issues, measures, and experts’ opinions, ORSA Journal on Computing, 5, 1, 2-18 (1993) · Zbl 0775.65029
[27] Barreto, L.; Bauer, M., Parallel branch and bound algorithm - a comparison between serial, OpenMP and MPI implementations, Journal of Physics: Conference Series, 256, 1, 012018 (2010)
[28] Baumelt, Z.; Dvorak, J.; Sucha, P.; Hanzalek, Z., A novel approach for nurse rerostering based on a parallel algorithm, European Journal of Operational Research, 251, 2, 624-639 (2016) · Zbl 1346.90468
[29] Ben Mabrouk, B.; Hasni, H.; Mahjoub, Z., On a parallel genetic-tabu search based algorithm for solving the graph colouring problem, European Journal of Operational Research, 197, 3, 1192-1201 (2009) · Zbl 1176.90482
[30] Benedicic, L.; Stular, M.; Korosec, P., A GPU-based parallel-agent optimization approach for the service coverage problem in UMTS networks, Computing and Informatics, 33, 5, 1025-1046 (2014)
[31] Borisenko, A.; Haidl, M.; Gorlatch, S., A GPU parallelization of branch-and-bound for multiproduct batch plants optimization, Journal of Supercomputing, 73, 2, 639-651 (2017)
[32] Borisenko, A.; Kegel, P.; Gorlatch, S., Optimal design of multi-product batch plants using a parallel branch-and-bound method, Proceedings of the 11th international conference on parallel computing technologies, 417-430 (2011), Springer-Verlag Berlin
[33] Boschetti, M. A.; Maniezzo, V.; Strappaveccia, F., Using GPU computing for solving the two-dimensional guillotine cutting problem, INFORMS Journal on Computing, 28, 3, 540-552 (2016) · Zbl 1348.90501
[34] Boukedjar, A.; Lalami, M. E.; El-Baz, D., Parallel branch and bound on a CPU-GPU system, Proceedings of the 20th euromicro international conference on parallel, distributed and network-based processing (pdp), 392-398 (2012)
[35] Boyer, V.; El Baz, D., Recent advances on GPU computing in operations research, Proceedings of the 27th international conference on parallel & distributed processing symposium, 1778-1787 (2013)
[36] Boyer, V.; El Baz, D.; Elkihel, M., Solving knapsack problems on GPU, Computers & Operations Research, 39, 1, 42-47 (2012) · Zbl 1251.90014
[37] Bozdağ, D.; Gebremedhin, A. H.; Manne, F.; Boman, E. G.; Catalyurek, U. V., A framework for scalable greedy coloring on distributed-memory parallel computers, Journal of Parallel and Distributed Computing, 68, 4, 515-535 (2008) · Zbl 1243.68314
[38] Bożejko, W., Solving the flow shop problem by parallel programming, Journal of Parallel and Distributed Computing, 69, 5, 470-481 (2009)
[39] Bozejko, W.; Gnatowski, A.; Pempera, J.; Wodecki, M., Parallel tabu search for the cyclic job shop scheduling problem, Computers & Industrial Engineering, 113, 512-524 (2017)
[40] Bożejko, W.; Pempera, J.; Smutnicki, C., Parallel simulated annealing for the job shop scheduling problem, Proceedings of the 9th international conference on computational science, 631-640 (2009), Springer-Verlag Berlin
[41] Bozejko, W.; Pempera, J.; Smutnicki, C., Parallel tabu search algorithm for the hybrid flow shop problem, Computers & Industrial Engineering, 65, 3, 466-474 (2013)
[42] Bożejko, W.; Uchroński, M.; Wodecki, M., Parallel metaheuristics for the cyclic flow shop scheduling problem, Computers & Industrial Engineering, 95, 156-163 (2016)
[43] Brodtkorb, A. R.; Hagen, T. R.; Schulz, C.; Hasle, G., GPU computing in discrete optimization. Part I: Introduction to the GPU, EURO Journal on Transportation and Logistics, 2, 1-2, 129-157 (2013)
[44] Bukata, L.; Sucha, P.; Hanzalek, Z., Solving the resource constrained project scheduling problem using the parallel tabu search designed for the CUDA platform, Journal of Parallel and Distributed Computing, 77, 58-68 (2015)
[45] New York, NY, USA. doi:10.1145/2145816.2145883.
[46] Cantú-Paz, E., A survey of parallel genetic algorithms, Calculateurs Paralleles, Reseaux Et Systems Repartis, 10, 2, 141-171 (1998)
[47] Cant-Paz, E., Theory of parallel genetic algorithms chapter 18,, 423-445 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey
[48] Cao, B.; Zhao, J.; Lv, Z.; Liu, X., A distributed parallel cooperative coevolutionary multiobjective evolutionary algorithm for large-scale optimization, IEEE Transactions on Industrial Informatics, 13, 4, 2030-2038 (2017)
[49] Carneiro, T.; Muritiba, A. E.; Negreiros, M.; de Campos, G. A.L., A new parallel schema for branch-and-bound algorithms using GPGPU, Proceedings of the 23rd international symposium on computer architecture and high performance computing, 41-47 (2011)
[50] Carvajal, R.; Ahmed, S.; Nemhauser, G.; Furman, K.; Goel, V.; Shao, Y., Using diversification, communication and parallelism to solve mixed-integer linear programs, Operations Research Letters, 42, 2, 186-189 (2014) · Zbl 1408.90194
[51] Cauley, S.; Balakrishnan, V.; Hu, Y. C.; Koh, C.-k., A parallel branch-and-cut approach for detailed placement, ACM Transactions on Design Automation of Electronic Systems, 16, 2 (2011)
[52] Cecilia, J. M.; Garcia, J. M.; Nisbet, A.; Amos, M.; Ujaldon, M., Enhancing data parallelism for ant colony optimization on GPUs, Journal of Parallel and Distributed Computing, 73, 1, SI, 42-51 (2013)
[53] Cecilia, J. M.; Garcia, J. M.; Ujaldon, M.; Nisbet, A.; Amos, M., Parallelization strategies for ant colony optimisation on GPUs, Proceedings of the 25th international conference on parallel & distributed processing symposium, 339-346 (2011)
[54] Chakroun, I.; Melab, N., Towards a heterogeneous and adaptive parallel branch-and-bound algorithm, Journal of Computer and System Sciences, 81, 1, SI, 72-84 (2015) · Zbl 1410.68378
[55] Chakroun, I.; Melab, N.; Mezmaz, M.; Tuyttens, D., Combining multi-core and GPU computing for solving combinatorial optimization problems, Journal of Parallel and Distributed Computing, 73, 12, SI, 1563-1577 (2013)
[56] Chakroun, I.; Mezmaz, M.; Melab, N.; Bendjoudi, A., Reducing thread divergence in a GPU-accelerated branch-and-bound algorithm, Concurrency and Computation-practice & Experience, 25, 8, SI, 1121-1136 (2013)
[57] Chaves-Gonzalez, J. M.; Vega-Rodriguez, M. A.; Gomez-Pulido, J. A.; Sanchez-Perez, J. M., Optimizing a realistic large-scale frequency assignment problem using a new parallel evolutionary approach, Engineering Optimization, 43, 8, 813-842 (2011)
[58] Christou, I. T.; Vassilaras, S., A parallel hybrid greedy branch and bound scheme for the maximum distance-2 matching problem, Computers & Operations Research, 40, 10, 2387-2397 (2013) · Zbl 1348.90592
[59] Coelho, I. M.; Munhoz, P. L.A.; Ochi, L. S.; Souza, M. J.F.; Bentes, C.; Farias, R., An integrated CPU-GPU heuristic inspired on variable neighbourhood search for the single vehicle routing problem with deliveries and selective pickups, International Journal of Production Research, 54, 4, 945-962 (2016)
[60] Cordeau, J.-F.; Maischberger, M., A parallel iterated tabu search heuristic for vehicle routing problems, Computers & Operations Research, 39, 9, 2033-2050 (2012)
[61] Cotta, C.; Talbi, E.-G.; Alba, E., Parallel hybrid metaheuristics chapter 15,, 347-370 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey · Zbl 1137.90724
[62] Crainic, T.; Toulouse, M., Learning and intelligent optimization. (2008), Springer, Berlin. volume 5315 of Lecture Notes in Computer Science. chapter Explicit and emergent cooperation schemes for search algorithms. pp. 95109
[63] Crainic, T. G., Parallel solution methods for vehicle routing problems, The vehicle routing problem: Latest advances and new challenges, 171-198 (2008), Springer, Boston, MA · Zbl 1187.90046
[64] Crainic, T. G., Parallel Meta-heuristic Search, (Martí, R.; Panos, P.; Resende, M. G., Handbook of heuristics (2018), Springer: Springer Cham), 1-39
[65] Crainic, T. G., Parallel metaheuristics and cooperative search, (Gendreau, M.; Potvin, J. -Y., Handbook of metaheuristics (2019), Springer), 419-451
[66] Crainic, T. G.; Davidović, T.; Ramljak, D., Designing parallel meta-heuristic methods, (Despotovic-Zrakic, M.; Milutinovic, V.; Belic, A., Handbook of Research on High Performance and Cloud Computing in Scientific Research and Education (2014), IGI Global: IGI Global Hershey, PA), 260-280
[67] Crainic, T. G.; Gendreau, M.; Potvin, J.-Y., Parallel tabu search chapter 13,, 289-313 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey · Zbl 1137.90725
[68] Crainic, T. G.; Hail, N., Parallel metaheuristics applications, ((2005), John Wiley & Sons, Inc., Hoboken, New Jersey), 447-494 · Zbl 1137.90023
[69] Crainic, T. G.; Le Cun, B.; Roucairol, C., Parallel combinatorial optimization chapter 1,, 1-28 (2006), John Wiley & Sons, Inc., Hoboken, New Jersey
[70] Crainic, T. G.; Toulouse, M., Parallel strategies for meta-heuristics, Handbook of metaheuristics, 475-513 (2003), Springer, Boston, MA · Zbl 1053.90138
[71] Crainic, T. G.; Toulouse, M., Parallel meta-heuristics, (Gendreau, M.; Potvin, J. -Y., Handbook of metaheuristics (2010), Springer), 497-541
[72] Cung, V.-D.; Martins, S. L.; Ribeiro, C. C.; Roucairol, C., Strategies for the parallel implementation of metaheuristics, Essays and surveys in metaheuristics, 263-308 (2002), Springer, Boston, MA · Zbl 1005.90066
[73] Czapinski, M., Parallel simulated annealing with genetic enhancement for flowshop problem with CSUM, Computers & Industrial Engineering, 59, 4, 778-785 (2010)
[74] Czapiński, M., An effective parallel multistart tabu search for quadratic assignment problem on CUDA platform, Journal of Parallel and Distributed Computing, 73, 11, 1461-1468 (2013)
[75] Czapinski, M.; Barnes, S., Tabu search with two approaches to parallel flowshop evaluation on CUDA platform, Journal of Parallel and Distributed Computing, 71, 6, SI, 802-811 (2011)
[76] Dai, C.; Toulouse, M.; Li, B. P.C., A multilevel cooperative tabu search algorithm for the covering design problem, The Journal of Combinatorial Mathematics and Combinatorial Computing, 68, February, 35-65 (2009) · Zbl 1176.05012
[77] Davidović, T.; Crainic, T. G., MPI parallelization of variable neighborhood search, Electronic Notes in Discrete Mathematics, 39, 241-248 (2012) · Zbl 1268.68150
[78] Davidovic, T.; Ramljak, D.; Šelmic, M.; Teodorovic, D., Mpi parallelization of bee colony optimization, Proceedings of the 1st international symposium & 10th balkan conference on operational research, 2, 193-200 (2011)
[79] Deep, K.; Sharma, S.; Pant, M., Modified parallel particle swarm optimization for global optimization using message passing interface, Proceedings of the 5th international conference on bio-inspired computing: Theories and applications (bic-ta), 1451-1458 (2010)
[80] Defersha, F. M., A simulated annealing with multiple-search paths and parallel computation for a comprehensive flowshop scheduling problem, International Transactions in Operational Research, 22, 4, 669-691 (2015) · Zbl 1332.90108
[81] Defersha, F. M.; Chen, M., A parallel genetic algorithm for dynamic cell formation in cellular manufacturing systems, International Journal of Production Research, 46, 22, 6389-6413 (2008) · Zbl 1154.90540
[82] Defersha, F. M.; Chen, M., A parallel genetic algorithm for a flexible job-shop scheduling problem with sequence dependent setups, International Journal of Advanced Manufacturing Technology, 49, 1-4, 263-279 (2010)
[83] Defersha, F. M.; Chen, M., Mathematical model and parallel genetic algorithm for hybrid flexible flowshop lot streaming problem, International Journal of Advanced Manufacturing Technology, 62, 1-4, 249-265 (2012)
[84] Delevacq, A.; Delisle, P.; Gravel, M.; Krajecki, M., Parallel ant colony optimization on graphics processing units, Journal of Parallel and Distributed Computing, 73, 1, SI, 52-61 (2013)
[85] Derbel, B.; Humeauc, J.; Liefooghe, A.; Verel, S., Distributed localized bi-objective search, European Journal of Operational Research, 239, 3, 731-743 (2014) · Zbl 1339.90295
[86] Dias, B. H.; Tomim, M. A.; Marques Marcato, A. L.; Ramos, T. P.; Brandi, R. B.S.; Da Silva Junior, I. C.; Passos Filho, J. A., Parallel computing applied to the stochastic dynamic programming for long term operation planning of hydrothermal power systems, European Journal of Operational Research, 229, 1, 212-222 (2013) · Zbl 1317.90345
[87] Diaz, J.; Munoz-Caro, C.; Nino, A., A survey of parallel programming models and tools in the multi and many-core era, IEEE Transactions on parallel and distributed systems, 23, 8, 1369-1386 (2012)
[88] Diego, F. J.; Gómez, E. M.; Ortega-Mier, M.; García-Sánchez, Á., Parallel CUDA architecture for solving de VRP with ACO, Industrial engineering: Innovative networks, 385-393 (2012), Springer, Boston, MA
[89] Ding, K.; Zheng, S.; Tan, Y., A GPU-based parallel fireworks algorithm for optimization, Proceedings of the 15th annual conference on genetic and evolutionary computation, 9-16 (2013)
[90] Djerrah, A.; Le Cun, B.; Cung, V.-D.; Roucairol, C., Bob++: Framework for solving optimization problems with branch-and-bound methods, Proceedings of the 15th IEEE international conference on high performance distributed computing, 369-370 (2006)
[91] Dobrian, F.; Gebremedhin, A.; Halappanavar, M.; Pothen, A., Distributed-memory parallel algorithms for matching and coloring, Proceedings of the 26th international parallel and distributed processing symposium workshops & phd forum, 1971-1980 (2011)
[92] Dongdong, G.; Guanghong, G.; Liang, H.; Ni, L., Application of multi-core parallel ant colony optimization in target assignment problem, Proceedings of the 2010 international conference on computer application and system modeling (ICCASM), 3, V3-514 (2010)
[93] Dorigo, M.; Stutzle, T., Ant colony optimization (2004), MIT Press · Zbl 1092.90066
[94] Dorronsoro, B.; Danoy, G.; Nebro, A. J.; Bouvry, P., Achieving super-linear performance in parallel multi-objective evolutionary algorithms by means of cooperative coevolution, Computers & Operations Research, 40, 6, SI, 1552-1563 (2013) · Zbl 1348.90635
[95] Eckstein, J.; Hart, W. E.; Phillips, C. A., PEBBL: An object-oriented framework for scalable parallel branch and bound, Mathematical Programming Computation, 7, 4, 429-469 (2015) · Zbl 1329.90171
[96] Eskandarpour, M.; Zegordi, S. H.; Nikbakhsh, E., A parallel variable neighborhood search for the multi-objective sustainable post-sales network design problem, International Journal of Production Economics, 145, 1, 117-131 (2013)
[97] Fabris, F.; Krohling, R. A., A co-evolutionary differential evolution algorithm for solving min-max optimization problems implemented on GPU using c-CUDA, Expert Systems with Applications, 39, 12, 10324-10333 (2012)
[98] Ferreiro, A. M.; Garcia, J. A.; Lopez-Salas, J. G.; Vazquez, C., An efficient implementation of parallel simulated annealing algorithm in GPUs, Journal of Global Optimization, 57, 3, SI, 863-890 (2013) · Zbl 1286.90115
[99] Figueira, J. R.; Liefooghe, A.; Talbi, E. G.; Wierzbicki, A. P., A parallel multiple reference point approach for multi-objective optimization, European Journal of Operational Research, 205, 2, 390-400 (2010) · Zbl 1188.90237
[100] Fujimoto, N.; Tsutsui, S., A highly-parallel TSP solver for a GPU computing platform, Proceedings of the 7th. international conference on numerical methods and applications, 264-271 (2011), Springer-Verlag Berlin
[101] Galea, F.; Le Cun, B., A parallel exact solver for the three-index quadratic assignment problem, Proceedings of the 2011 IEEE international symposium on parallel and distributed processing workshops and phd forum, 1940-1949 (2011)
[102] Gao, J.; He, G.; Wang, Y., A new parallel genetic algorithm for solving multiobjective scheduling problems subjected to special process constraint, International Journal of Advanced Manufacturing Technology, 43, 1-2, 151-160 (2009)
[103] (Gendreau, M.; Potvin, J. -Y.; etal., Handbook of metaheuristics International (vol. 146). Series in Operations Research & Management Science. (2010), Springer)
[104] (Gendreau, M.; Potvin, J. -Y.; etal., Handbook of metaheuristics (vol. 146). International Series in Operations Research & Management Science (2019), Springer)
[105] Gendron, B.; Crainic, T. G., Parallel branch-and-branch algorithms: survey and synthesis, Operations Research, 42, 6, 1042-1066 (1994) · Zbl 0824.90096
[106] Gerasch, T. E.; Wang, P. Y., A survey of parallel algorithms for one-dimensional integer knapsack problems, INFOR: Information Systems and Operational Research, 32, 3, 163-186 (1994) · Zbl 0811.90073
[107] Gmys, J.; Mezmaz, M.; Melab, N.; Tuyttens, D., A GPU-based branch-and-bound algorithm using integer-vector-matrix data structure, Parallel Computing, 59, SI, 119-139 (2016)
[108] Gmys, J.; Mezmaz, M.; Melab, N.; Tuyttens, D., Ivm-based parallel branch-and-bound using hierarchical work stealing on multi-GPU systems, Concurrency and Computation-practice & Experience, 29, 9, SI (2017)
[109] Gomes, F. C.; Meneses, C. N.; Pardalos, P. M.; Viana, G. V.R., A parallel multistart algorithm for the closest string problem, Computers & Operations Research, 35, 11, 3636-3643 (2008) · Zbl 1209.92024
[110] Groer, C.; Golden, B.; Wasil, E., A parallel algorithm for the vehicle routing problem, INFORMS Journal on Computing, 23, 2, 315-330 (2011) · Zbl 1243.90186
[111] Hadian, A.; Shahrivari, S.; Minaei-Bidgoli, B., Fine-grained parallel ant colony system for shared-memory architectures, International Journal of Computer Applications, 53, 8 (2012)
[112] He, J.; Chang, D.; Mi, W.; Yan, W., A hybrid parallel genetic algorithm for yard crane scheduling, Transportation Research Part E-logistics and Transportation Review, 46, 1, 136-155 (2010)
[113] Hemmelmayr, V. C., Sequential and parallel large neighborhood search algorithms for the periodic location routing problem, European Journal of Operational Research, 243, 1, 52-60 (2015) · Zbl 1346.90120
[114] Herrera, J. F.; Casado, L. G.; Hendrix, E. M.; Paulavicius, R.; Ilinskas, J., Dynamic and hierarchical load-balancing techniques applied to parallel branch-and-bound methods, Proceedings of the 8th international conference on p2p, parallel, grid, cloud and internet computing (3PGCIC), 497-502 (2013)
[115] Herrera, J. F.R.; Salmeron, J. M.G.; Hendrix, E. M.T.; Asenjo, R.; Casado, L. G., On parallel branch and bound frameworks for global optimization, Journal of Global Optimization, 69, 3, 547-560 (2017) · Zbl 1386.68213
[116] Hifi, M.; Negre, S.; Saadi, T.; Saleh, S.; Wu, L., A parallel large neighborhood search-based heuristic for the disjunctively constrained knapsack problem, Proceedings of the 2014 IEEE international parallel & distributed processing symposium workshops, 1547-1551 (2014)
[117] Homberger, J., A parallel genetic algorithm for the multilevel unconstrained lot-sizing problem, INFORMS Journal on Computing, 20, 1, 124-132 (2008) · Zbl 1243.90063
[118] Hong, L.; Zhong-hua, L.; Xue-bin, C., Parallel computing for dynamic asset allocation based on the stochastic programming, Proceedings of the 2010 WASE international conference on information engineering (ICIE), 2, 172-176 (2010)
[119] Hou, N.; He, F.; Zhou, Y.; Ai, H., A GPU-based tabu search for very large hardware/software partitioning with limited resource usage, Journal of Advanced Mechanical Design Systems and Manufacturing, 11, 5 (2017)
[120] Huang, C.-S.; Huang, Y.-C.; Lai, P.-J., Modified genetic algorithms for solving fuzzy flow shop scheduling problems and their implementation with CUDA, Expert Systems with Applications, 39, 5, 4999-5005 (2012)
[121] Huebner, J.; Schmidt, M.; Steinbach, M. C., A distributed interior-point KKT solver for multistage stochastic optimization, INFORMS Journal on Computing, 29, 4, 612-630 (2017)
[122] Hung, Y.; Wang, W., Accelerating parallel particle swarm optimization via GPU, Optimization Methods & Software, 27, 1, 33-51 (2012) · Zbl 1242.90300
[123] Ibri, S.; Drias, H.; Nourelfath, M., A parallel hybrid ant-tabu algorithm for integrated emergency vehicle dispatching and covering problem, International Journal of Innovative Computing and Applications, 2, 4, 226-236 (2010)
[124] INRIA (n.d.). Paradiseo - A Software Framewok for Metaheuristics. http://paradiseo.gforge.inria.fr.
[125] Ismail, M. A.; Mirza, S. H.; Altaf, T., A parallel and concurrent implementation of Lin-Kernighan heuristic (LKH-2) for solving traveling salesman problem for multi-core processors using SPC 3 programming model, International Journal of Advanced Computer Science and Applications, 2, 7, 34-43 (2011)
[126] Ismail, M. M.; Abd El-Raoof, O.; Abd El-Wahed, W. F., A parallel branch and bound algorithm for solving large scale integer programming problems, Applied Mathematics & Information Sciences, 8, 4, 1691-1698 (2014)
[127] Izzo, D.; Rucinski, M.; Ampatzis, C., Parallel global optimisation meta-heuristics using an asynchronous island-model, Proceedings of the IEEE congress on evolutionary computation, 2301-2308 (2009), IEEE
[128] James, T.; Rego, C.; Glover, F., A cooperative parallel tabu search algorithm for the quadratic assignment problem, European Journal of Operational Research, 195, 3, 810-826 (2009) · Zbl 1156.90400
[129] Janiak, A.; Janiak, W.; Lichtenstein, M., Tabu search on GPU, Journal of Universal Computer Science, 14, 14, 2416-2427 (2008)
[130] Janson, S.; Merkle, D.; Middendorf, M., Parallel ant colony algorithms chapter 3,, 171-201 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey · Zbl 1278.90468
[131] Jin, J.; Crainic, T. G.; Løkketangen, A., A guided cooperative parallel tabu search for the capacitated vehicle routing problem, Proceedings of NIK 2011, 49-60 (2011)
[132] Jin, J.; Crainic, T. G.; Lokketangen, A., A parallel multi-neighborhood cooperative tabu search for capacitated vehicle routing problems, European Journal of Operational Research, 222, 3, 441-451 (2012)
[133] Jin, J.; Crainic, T. G.; Lokketangen, A., A cooperative parallel metaheuristic for the capacitated vehicle routing problem, Computers & Operations Research, 44, 33-41 (2014) · Zbl 1307.90024
[134] Juan, A. A.; Faulin, J.; Jorba, J.; Caceres, J.; Manuel Marques, J., Using parallel & distributed computing for real-time solving of vehicle routing problems with stochastic demands, Annals of Operations Research, 207, 1, 43-65 (2013) · Zbl 1272.90009
[135] Kang, S.; Kim, S.-S.; Won, J.; Kang, Y.-M., GPU-based parallel genetic approach to large-scale travelling salesman problem, Journal of Supercomputing, 72, 11, 4399-4414 (2016)
[136] Kerkhove, L. P.; Vanhoucke, M., A parallel multi-objective scatter search for optimising incentive contract design in projects, European Journal of Operational Research, 261, 3, 1066-1084 (2017)
[137] Knysh, D. S.; Kureichik, V. M., Parallel genetic algorithms: a survey and problem state of the art, Journal of Computer and Systems Sciences International, 49, 4, 579-589 (2010)
[138] Koc, U.; Mehrotra, S., Generation of feasible integer solutions on a massively parallel computer using the feasibility pump, Operations Research Letters, 45, 6, 652-658 (2017) · Zbl 1409.90117
[139] Kollias, G.; Sathe, M.; Schenk, O.; Grama, A., Fast parallel algorithms for graph similarity and matching, Journal of Parallel and Distributed Computing, 74, 5, 2400-2410 (2014)
[140] Ku, M.-Y.; Hu, M. H.; Wang, M.-J., Simulated annealing based parallel genetic algorithm for facility layout problem, International Journal of Production Research, 49, 6, 1801-1812 (2011)
[141] Kumar, S.; Misra, A.; Tomar, R. S., A modified parallel approach to single source shortest path problem for massively dense graphs using CUDA, Proceedings of the 2nd international conference on computer and communication technology (ICCCT), 635-639 (2011)
[142] Laguna-Sanchez, G. A.; Olguin-Carbajal, M.; Cruz-Cortes, N.; Barron-Fernandez, R.; Alvarez-Cedillo, J. A., Comparative study of parallel variants for a particle swarm optimization algorithm implemented on a multithreading GPU, Journal of Applied Research and Technology, 7, 3, 292-309 (2009)
[143] Lahrichi, N.; Crainic, T. G.; Gendreau, M.; Rei, W.; Crişan, G. C.; Vidal, T., An integrative cooperative search framework for multi-decision-attribute combinatorial optimization: Application to the MDPVRP, European Journal of Operational Research, 246, 2, 400-412 (2015) · Zbl 1346.90706
[144] Lancinskas, A.; Martinez Ortigosa, P.; Zilinskas, J., Parallel optimization algorithm for competitive facility location, Mathematical Modelling and Analysis, 20, 5, 619-640 (2015)
[145] Lančinskas, A.; Żilinskas, J., Solution of multi-objective competitive facility location problems using parallel NSGA-II on large scale computing systems, Proceedings of the 11th international conference on applied parallel computing, 422-433 (2012), Springer-Verlag Berlin
[146] Lančinskas, A.; Žilinskas, J., Parallel multi-objective memetic algorithm for competitive facility location, Proceedings of the 10th international conference on parallel processing and applied mathematics, 354-363 (2013), Springer-Verlag Berlin
[147] Lazarova, M.; Borovska, P., Comparison of parallel metaheuristics for solving the TSP, Proceedings of the 9th international conference on computer systems and technologies and workshop for phd students in computing, 17 (2008)
[148] Lei, D.; Guo, X., A parallel neighborhood search for order acceptance and scheduling in flow shop environment, International Journal of Production Economics, 165, 12-18 (2015)
[149] Li, C.-C.; Lin, C.-H.; Liu, J.-C., Parallel genetic algorithms on the graphics processing units using island model and simulated annealing, Advances in Mechanical Engineering, 9, 7 (2017)
[150] Li, K.; Liu, J.; Wan, L.; Yin, S.; Li, K., A cost-optimal parallel algorithm for the 0-1 knapsack problem and its performance on multicore CPU and GPU implementations, Parallel Computing, 43, 27-42 (2015)
[151] Limmer, S.; Fey, D., Comparison of common parallel architectures for the execution of the island model and the global parallelization of evolutionary algorithms, Concurrency and Computation: Practice and Experience, 29, 9 (2017), 31 pages
[152] Ling, C.; Hai-Ying, S.; Shu, W., A parallel ant colony algorithm on massively parallel processors and its convergence analysis for the travelling salesman problem, Information Sciences, 199, 31-42 (2012) · Zbl 1248.90076
[153] Liu, K.-H.; Kao, J.-J., Parallelised branch-and-bound algorithm for raster-based landfill siting, Civil Engineering and Environmental Systems, 30, 1, 15-25 (2013)
[154] Liu, Y. Y.; Cho, W. K.T.; Wang, S., Pear: a massively parallel evolutionary computation approach for political redistricting optimization and analysis, Swarm and Evolutionary Computation, 30, 78-92 (2016)
[155] Liu, Y. Y.; Wang, S., A scalable parallel genetic algorithm for the generalized assignment problem, Parallel Computing, 46, 98-119 (2015)
[156] Lootsma, F. A.; Ragsdell, K. M., State-of-the-art in parallel nonlinear optimization, Parallel Computing, 6, 2, 133-155 (1988) · Zbl 0633.65057
[157] Lou, Z.; Reinitz, J., Parallel simulated annealing using an adaptive resampling interval, Parallel Computing, 53, 23-31 (2016)
[158] Lu, H.; Liu, J.; Niu, R.; Zhu, Z., Fitness distance analysis for parallel genetic algorithm in the test task scheduling problem, Soft Computing, 18, 12, 2385-2396 (2014)
[159] Lubin, M.; Martin, K.; Petra, C. G.; Sandikci, B., On parallelizing dual decomposition in stochastic integer programming, Operations Research Letters, 41, 3, 252-258 (2013) · Zbl 1286.90102
[160] Lubin, M.; Petra, C. G.; Anitescu, M., The parallel solution of dense saddle-point linear systems arising in stochastic programming, Optimization Methods and Software, 27, 4-5, 845-864 (2012) · Zbl 1254.90140
[161] Lucka, M.; Melichercik, I.; Halada, L., Application of multistage stochastic programs solved in parallel in portfolio management, Parallel Computing, 34, 6-8, 469-485 (2008)
[162] Luna, F.; Alba, E.; Nebro, A. J., Parallel heterogeneous metaheuristics, 395-422 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey · Zbl 1137.90024
[163] Luo, G.-H.; Huang, S.-K.; Chang, Y.-S.; Yuan, S.-M., A parallel bees algorithm implementation on GPU, Journal of Systems Architecture, 60, 3, 271-279 (2014)
[164] Luo, J.; Hong, L. J.; Nelson, B. L.; Wu, Y., Fully sequential procedures for large-scale ranking-and-selection problems in parallel computing environments, Operations Research, 63, 5, 1177-1194 (2015) · Zbl 1347.68151
[165] Luque, G.; Alba, E.; Dorronsoro, B., Parallel genetic algorithms chapter 5,, 105-125 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey
[166] Lopez, F. G.; Torres, M. G.; Batista, B. M.; Perez, J. A.M.; Vega, J. M.M., Parallel scatter search chapter 10,, 223-246 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey · Zbl 1146.90500
[167] Maischberger, M.; Cordeau, J.-F., Solving variants of the vehicle routing problem with a simple parallel iterated tabu search, Network optimization, 395-400 (2011), Springer-Verlag Berlin · Zbl 1345.90111
[168] Maleki, S.; Musuvathi, M.; Mytkowicz, T., Efficient parallelization using rank convergence in dynamic programming algorithms, Communications of the ACM, 59, 10, 85-92 (2016)
[169] Martins, S. L.; Ribeiro, C. C., Metaheuristics and applications to optimization problems in telecommunications, Handbook of optimization in telecommunications, 103-128 (2006), Springer, Boston, MA · Zbl 1118.90059
[170] Massobrio, R.; Toutouh, J.; Nesmachnow, S.; Alba, E., Infrastructure deployment in vehicular communication networks using a parallel multiobjective evolutionary algorithm, International Journal of Intelligent Systems, 32, 8, 801-829 (2017)
[171] McCreesh, C.; Prosser, P., A parallel branch and bound algorithm for the maximum labelled clique problem, Optimization Letters, 9, 5, 949-960 (2015) · Zbl 1328.90127
[172] Melab, N.; Luong, T.; Boufaras, K.; Talbi, E.-G., Towards ParadisEO-MO-GPU: a framework for GPU-based local search metaheuristics, Proceedings of the international work-conference on artificial neural networks, 401-408 (2011), Springer
[173] Melab, N.; Talbi, E.-g.; Cahon, S.; Alba, E.; Luque, G., Parallel metaheuristics: Algorithms and frameworks chapter 6,, 149-161 (2006), John Wiley & Sons, Inc., Hoboken, New Jersey
[174] Menendez, B.; Pardo, E. G.; Sanchez-Oro, J.; Duarte, A., Parallel variable neighborhood search for the min-max order batching problem, International Transactions in Operational Research, 24, 3, 635-662 (2017) · Zbl 1366.90130
[175] Mezmaz, M.; Leroy, R.; Melab, N.; Tuyttens, D., A multi-core parallel branch-and-bound algorithm using factorial number system, Proceedings of the 28th international symposium on parallel and distributed processing, 1203-1212 (2014)
[176] Mezmaz, M.; Melab, N.; Kessaci, Y.; Lee, Y. C.; Talbi, E. G.; Zomaya, A. Y.; Tuyttens, D., A parallel bi-objective hybrid metaheuristic for energy-aware scheduling for cloud computing systems, Journal of Parallel and Distributed Computing, 71, 11, 1497-1508 (2011)
[177] Mu, D.; Wang, C.; Zhao, F.; Sutherland, J. W., Solving vehicle routing problem with simultaneous pickup and delivery using parallel simulated annealing algorithm, International Journal of Shipping and Transport Logistics, 8, 1, 81-106 (2016)
[178] Munawar, A.; Wahib, M.; Munetomo, M.; Akama, K., Hybrid of genetic algorithm and local search to solve MAX-SAT problem using nvidia CUDA framework, Genetic Programming and Evolvable Machines, 10, 4, 391-415 (2009)
[179] Mussi, L.; Daolio, F.; Cagnoni, S., Evaluation of parallel particle swarm optimization algorithms within the CUDA architecture, Information Sciences, 181, 20, 4642-4657 (2011)
[180] Nebro, A. J.; Durillo, J. J., A study of the parallelization of the multi-objective metaheuristic MOEA/D, Proceedings of the 11th international conference on learning and intelligent optimization, 303-317 (2010), Springer-Verlag Berlin
[181] Nebro, A. J.; Luna, F.; Talbi, E.-g.; Alba, E., Parallel multiobjective optimization chapter 16,, 371-394 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey · Zbl 1137.90656
[182] Nesmachnow, S.; Cancela, H.; Alba, E., A parallel micro evolutionary algorithm for heterogeneous computing and grid scheduling, Applied Soft Computing, 12, 2, 626-639 (2012)
[183] Nesmachnow, S.; Cancela, H.; Alba, E.; Chicano, F., Parallel metaheuristics in telecommunications chapter 20,, 495-515 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey · Zbl 1137.90741
[184] Nowotniak, R.; Kucharski, J., GPU-based massively parallel implementation of metaheuristic algorithms, Automatyka/Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie, 15, 595-611 (2011)
[185] Nwana, V.; Mitra, Parallel mixed integer programming: a status review, Technical Report (2000), Department of Mathematical Sciences, Brunel University
[186] Olensek, J.; Tuma, T.; Puhan, J.; Burmen, A., A new asynchronous parallel global optimization method based on simulated annealing and differential evolution, Applied Soft Computing, 11, 1, 1481-1489 (2011)
[187] Ozden, S. G.; Smith, A. E.; Gue, K. R., Solving large batches of traveling salesman problems with parallel and distributed computing, Computers & Operations Research, 85, 87-96 (2017) · Zbl 1458.90558
[188] Pages-Bernaus, A.; Perez-Valdes, G.; Tomasgard, A., A parallelised distributed implementation of a branch and fix coordination algorithm, European Journal of Operational Research, 244, 1, 77-85 (2015) · Zbl 1346.90644
[189] Pardalos, P. M.; Pitsoulis, L.; Mavridou, T.; Resende, M. G.C., Parallel search for combinatorial optimization: genetic algorithms, simulated annealing, tabu search and GRASP, Proceedings of the 2nd international workshop on parallel algorithms for irregularly structured problems, 317-331 (1995)
[190] Patvardhan, C.; Bansal, S.; Srivastav, A., Parallel improved quantum inspired evolutionary algorithm to solve large size quadratic knapsack problems, Swarm and Evolutionary Computation, 26, 175-190 (2016)
[191] Paulavičius, R.; Žilinskas, J., Parallel branch and bound algorithm with combination of Lipschitz bounds over multidimensional simplices for multicore computers, Parallel scientific computing and optimization, 93-102 (2009), Springer, Boston, MA · Zbl 1188.68353
[192] Paulavicius, R.; Zilinskas, J.; Grothey, A., Parallel branch and bound for global optimization with combination of lipschitz bounds, Optimization Methods & Software, 26, 3, 487-498 (2011)
[193] Pedemonte, M.; Nesmachnow, S.; Cancela, H., A survey on parallel ant colony optimization, Applied Soft Computing, 11, 8, 5181-5197 (2011)
[194] Pedroso, D. M.; Bonyadi, M. R.; Gallagher, M., Parallel evolutionary algorithm for single and multi-objective optimisation: differential evolution and constraints handling, Applied Soft Computing, 61, 995-1012 (2017)
[195] Polacek, M.; Benkner, S.; Doerner, K. F.; Hartl, R. F., A cooperative and adaptive variable neighborhood search for the multi depot vehicle routing problem with time windows, Business Research, 1, 2, 207-218 (2008)
[196] Polat, O., A parallel variable neighborhood search for the vehicle routing problem with divisible deliveries and pickups, Computers & Operations Research, 85, 71-86 (2017) · Zbl 1458.90129
[197] Ponz-Tienda, J. L.; Salcedo-Bernal, A.; Pellicer, E., A parallel branch and bound algorithm for the resource leveling problem with minimal lags, Computer-aided Civil and Infrastructure Engineering, 32, 6, 474-498 (2017)
[198] Posypkin, M. A.; Sigal, I. K., A combined parallel algorithm for solving the knapsack problem, Journal of Computer and Systems Sciences International, 47, 4, 543-551 (2008) · Zbl 1180.90277
[199] Prez, J. A.M.; Hansen, P.; Mladenovi, N., Parallel variable neighborhood search chapter 11,, 247-266 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey
[200] Qu, J.; Liu, X.; Sun, M.; Qi, F., GPU-based parallel particle swarm optimization methods for graph drawing, Discrete Dynamics in Nature and Society (2017)
[201] Quan, Z.; Wu, L., Design and evaluation of a parallel neighbor algorithm for the disjunctively constrained knapsack problem, Concurrency and Computation-practice & Experience, 29, 20, SI (2017)
[202] Randall, M.; Lewis, A., A parallel implementation of ant colony optimization, Journal of Parallel and Distributed Computing, 62, 9, 1421-1432 (2002) · Zbl 1063.68095
[203] Rao, Z.-S.; Zhu, W.-Y.; Zhang, K., Solving Graph Coloring Problem Using Parallel Discrete Particle Swarm Optimization on CUDA, Proceedings of the 2nd International Conference on Applied Mathematics, Simulation and Modelling (AMSM 2017), 236-240 (2017)
[204] Rashid, H.; Novoa, C.; Qasem, A., An evaluation of parallel knapsack algorithms on multicore architectures, Proceedings of the 2010 international conference on scientific computing, 230-235 (2010)
[205] Ravetti, M. G.; Riveros, C.; Mendes, A.; Resende, M. G.C.; Pardalos, P. M., Parallel hybrid heuristics for the permutation flow shop problem, Annals of Operations Research, 199, 1, 269-284 (2012) · Zbl 1251.90180
[206] Redondo, J. L.; Fernandez, J.; Garcia, I.; Ortigosa, P. M., Parallel algorithms for continuous competitive location problems, Optimisation Methods & Software, 23, 5, 779-791 (2008) · Zbl 1154.90532
[207] Redondo, J. L.; Garcia, I.; Ortigosa, P. M., Parallel evolutionary algorithms based on shared memory programming approaches, Journal of Supercomputing, 58, 2, SI, 270-279 (2011)
[208] Redondo, J. L.; Marin, A.; Ortigosa, P. M., A parallelized lagrangean relaxation approach for the discrete ordered median problem, Annals of Operations Research, 246, 1-2, 253-272 (2016) · Zbl 1357.90077
[209] Resende, M. G.C.; Ribeiro, C. C., Parallel greedy randomized adaptive search procedures chapter 14,, 315-346 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey · Zbl 1137.90742
[210] Roberge, V.; Tarbouchi, M.; Labonte, G., Comparison of parallel genetic algorithm and particle swarm optimization for real-time UAV path planning, IEEE Transactions on Industrial Informatics, 9, 1, 132-141 (2013)
[211] Rossbory, M.; Reisner, W., Parallelization of algorithms for linear discrete optimization using paraphrase, Proceedings of the 24th international workshop on database and expert systems applications (dexa), 241-245 (2013)
[212] Rudek, R., Exact and parallel metaheuristic algorithms for the single processor total weighted completion time scheduling problem with the sum-of-processing-time based models, Computers & Operations Research, 46, 91-101 (2014) · Zbl 1348.68024
[213] Rudolph, G., Parallel evolution strategies chapter 7,, 155-169 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey · Zbl 1278.90477
[214] Sancı, S.; İşler, V., A parallel algorithm for UAV flight route planning on GPU, International Journal of Parallel Programming, 39, 6, 809-837 (2011)
[215] Sanjuan-Estrada, J.; Casado, L. G.; García, I., Adaptive parallel interval global optimization algorithms based on their performance for non-dedicated multicore architectures, Proceedings of the 19th euromicro international conference on parallel, distributed and network-based processing (PDP), 252-256 (2011)
[216] Santos, L.; Madeira, D.; Clua, E.; Martins, S.; Plastino, A., A parallel GRASP resolution for a GPU architecture, Proceedings of the 7th international conference on metaheuristics and nature inspired computing, META10 (2010)
[217] Sathe, M.; Schenk, O.; Burkhart, H., An auction-based weighted matching implementation on massively parallel architectures, Parallel Computing, 38, 12, 595-614 (2012)
[218] Scheerlinck, K.; Vernieuwe, H.; De Baets, B., Zadeh’s extension principle for continuous functions of non-interactive variables: a parallel optimization approach, IEEE Transactions on Fuzzy Systems, 20, 1, 96-108 (2012)
[219] Schulz, C.; Hasle, G.; Brodtkorb, A. R.; Hagen, T. R., GPU computing in discrete optimization: Part II: Survey focused on routing problems, EURO Journal on Transportation and Logistics, 2, 159-186 (2013)
[220] Shylo, O. V.; Middelkoop, T.; Pardalos, P. M., Restart strategies in optimization: parallel and serial cases, Parallel Computing, 37, 1, 60-68 (2011) · Zbl 1211.68507
[221] Silva, J. M.N.; Boeres, C.; Drummond, L. M.A.; Pessoa, A. A., Memory aware load balance strategy on a parallel branch-and-bound application, Concurrency and Computation-practice & Experience, 27, 5, 1122-1144 (2015)
[222] Skinderowicz, R., The GPU-based parallel ant colony system, Journal of Parallel and Distributed Computing, 98, 48-60 (2016)
[223] Stanojevic, P.; Maric, M.; Stanimirovic, Z., A hybridization of an evolutionary algorithm and a parallel branch and bound for solving the capacitated single allocation hub location problem, Applied Soft Computing, 33, 24-36 (2015)
[224] Stivala, A.; Stuckey, P. J.; Garcia De La Banda, M.; Hermenegildo, M.; Wirth, A., Lock-free parallel dynamic programming, Journal of Parallel and Distributed Computing, 70, 8, 839-848 (2010) · Zbl 1233.68225
[225] Subotic, M.; Tuba, M.; Stanarevic, N., Different approaches in parallelization of the artificial bee colony algorithm, International Journal of Mathematical Models and Methods in Applied Sciences, 5, 4, 755-762 (2011)
[226] Subramanian, A.; Drummond, L. M.A.; Bentes, C.; Ochi, L. S.; Farias, R., A parallel heuristic for the vehicle routing problem with simultaneous pickup and delivery, Computers & Operations Research, 37, 11, SI, 1899-1911 (2010) · Zbl 1188.90041
[227] (Talbi, E. -G., Parallel combinatorial optimization (2006), John Wiley & Sons)
[228] Talbi, E.-G., Metaheuristics: from design to implementation (2009), John Wiley & Sons · Zbl 1190.90293
[229] Tan, G.; Sun, N.; Gao, G. R., Improving performance of dynamic programming via parallelism and locality on multicore architectures, IEEE Transactions on Parallel and Distributed Systems, 20, 2, 261-274 (2009)
[230] Tan, Y.; Ding, K., A survey on GPU-based implementation of swarm intelligence algorithms, IEEE Transactions on Cybernetics, 46, 9, 2028-2041 (2016)
[231] Taoka, S.; Takafuji, D.; Watanabe, T., Enhancing PC cluster-based parallel branch-and-bound algorithms for the graph coloring problem, IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, E91A, 4, 1140-1149 (2008)
[232] Thiruvady, D.; Ernst, A. T.; Singh, G., Parallel ant colony optimization for resource constrained job scheduling, Annals of Operations Research, 242, 2, 355-372 (2016) · Zbl 1350.90013
[233] Tosun, U.; Dokeroglu, T.; Cosar, A., A robust island parallel genetic algorithm for the quadratic assignment problem, International Journal of Production Research, 51, 14, 4117-4133 (2013)
[234] Toulouse, M.; Crainic, T. G.; Sansó, B., Systemic behavior of cooperative search algorithms, Parallel Computing, 30, 1, 57-79 (2004)
[235] Toulouse, M.; Crainic, T. G.; Thulasiraman, K., Global optimization properties of parallel cooperative search algorithms: A simulation study, Parallel Computing, 26, 1, 91-112 (2000) · Zbl 1046.68136
[236] Tran, Q.-N., Designing efficient many-core parallel algorithms for all-pairs shortest-paths using CUDA, Proceedings of the 7th international conference on information technology: New generations (ITNG), 7-12 (2010)
[237] Trelles, O.; Rodriguez, A., Bioinformatics and parallel metaheuristics chapter 21,, 517-549 (2005), John Wiley & Sons, Inc., Hoboken, New Jersey · Zbl 1137.90025
[238] Tsutsui, S., Parallel ant colony optimization for the quadratic assignment problems with symmetric multi processing, Proceedings of the 6th international conference ant colony optimization and swarm intelligence, 363-370 (2008), Springer-Verlag Berlin
[239] Tu, W.; Li, Q.; Li, Q.; Zhu, J.; Zhou, B.; Chen, B., A spatial parallel heuristic approach for solving very large-scale vehicle routing problems, Transactions in GIS, 21, 6, 1130-1147 (2017)
[240] Umbarkar, A.; Joshi, M. S.; Hong, W.-C., Multithreaded parallel dual population genetic algorithm (MPDPGA) for unconstrained function optimizations on multi-core system, Applied Mathematics and Computation, 243, 936-949 (2014) · Zbl 1335.90119
[241] Vallada, E.; Ruiz, R., Cooperative metaheuristics for the permutation flowshop scheduling problem, European Journal of Operational Research, 193, 2, 365-376 (2009) · Zbl 1160.90488
[242] Van Luong, T.; Melab, N.; Talbi, E.-G., GPU computing for parallel local search metaheuristic algorithms, IEEE transactions on computers, 62, 1, 173-185 (2013) · Zbl 1365.68392
[243] Van Luong, T.; Taillard, E.; Melab, N.; Talbi, E.-G., Parallelization strategies for hybrid metaheuristics using a single GPU and multi-core resources, Proceedings of the 12th international conference on parallel problem solving from nature, 368-377 (2012), Springer-Verlag Berlin
[244] Vidal, P.; Alba, E.; Luna, F., Solving optimization problems using a hybrid systolic search on GPU plus CPU, Soft Computing, 21, 12, 3227-3245 (2017)
[245] Vu, T.-t.; Derbel, B., Parallel branch-and-bound in multi-core multi-CPU multi-GPU heterogeneous environments, Future Generation Computer Systems-the International Journal of Escience, 56, 95-109 (2016)
[246] Wang, C.; Mu, D.; Zhao, F.; Sutherland, J. W., A parallel simulated annealing method for the vehicle routing problem with simultaneous pickup-delivery and time windows, Computers & Industrial Engineering, 83, 111-122 (2015)
[247] Wang, D.; Wu, C.-H.; Ip, A.; Wang, D.; Yan, Y., Parallel multi-population particle swarm optimization algorithm for the uncapacitated facility location problem using OpenMP, Proceedings of the 2008 IEEE congress on evolutionary computation, 1214-1218 (2008)
[248] Wang, K.; Shen, Z., A GPU-based parallel genetic algorithm for generating daily activity plans, IEEE Trans. Intelligent Transportation Systems, 13, 3, 1474-1480 (2012)
[249] Weber, M.; Neri, F.; Tirronen, V., Shuffle or update parallel differential evolution for large-scale optimization, Soft Computing, 15, 11, 2089-2107 (2011)
[250] Wei, K.-c.; Sun, X.; Chu, H.; Wu, C.-C., Reconstructing permutation table to improve the tabu search for the PFSP on GPU, Journal of Supercomputing, 73, 11, 4711-4738 (2017)
[251] Xhafa, F.; Duran, B., Parallel memetic algorithms for independent job scheduling in computational grids, Recent advances in evolutionary computation for combinatorial optimization, 219-239 (2008), Springer-Verlag Berlin · Zbl 1159.68630
[252] Xu, Y.; Ralphs, T. K.; Ladanyi, L.; Saltzman, M. J., Computational experience with a software framework for parallel integer programming, INFORMS Journal on Computing, 21, 3, 383-397 (2009) · Zbl 1243.90010
[253] Yang, Q.; Fang, L.; Duan, X., RMACO: a randomly matched parallel ant colony optimization, World Wide Web: Internet and Web Information Systems, 19, 6, 1009-1022 (2016)
[254] Yazdani, M.; Amiri, M.; Zandieh, M., Flexible job-shop scheduling with parallel variable neighborhood search algorithm, Expert Systems with Applications, 37, 1, 678-687 (2010)
[255] You, Y.-S., Parallel ant system for traveling salesman problem on GPUs, Proceedings of 11th. international conference on genetic and evolutionary computation, 1-2 (2009)
[256] Yu, B.; Yang, Z.; Sun, X.; Yao, B.; Zeng, Q.; Jeppesen, E., Parallel genetic algorithm in bus route headway optimization, Applied Soft Computing, 11, 8, 5081-5091 (2011)
[257] Yu, B.; Yang, Z. Z.; Xie, J. X., A parallel improved ant colony optimization for multi-depot vehicle routing problem, Journal of the Operational Research Society, 62, 1, 183-188 (2011)
[258] Yu, W.-J.; Li, J.-Z.; Chen, W.-N.; Zhang, J., A parallel double-level multiobjective evolutionary algorithm for robust optimization, Applied Soft Computing, 59, 258-275 (2017)
[259] Zhang, X.-Y.; Zhang, J.; Gong, Y.-J.; Zhan, Z.-H.; Chen, W.-N.; Li, Y., Kuhnmunkres parallel genetic algorithm for the set cover problem and its application to large-scale wireless sensor networks, IEEE Transactions on Evolutionary Computation, 20, 5, 695-710 (2016)
[260] Zhang, Y.; Wang, S.; Ji, G., A comprehensive survey on particle swarm optimization algorithm and its applications, Mathematical Problems in Engineering, 2015 (2015) · Zbl 1394.90588
[261] Zhao, J.; Liu, Q.; Wang, W.; Wei, Z.; Shi, P., A parallel immune algorithm for traveling salesman problem and its application on cold rolling scheduling, Information Sciences, 181, 7, 1212-1223 (2011)
[262] Zhou, Y.; He, F.; Hou, N.; Qiu, Y., Parallel ant colony optimization on multi-core SIMD CPUs, Future Generation Computer Systems (2017)
[263] Zhu, W.; Curry, J., Parallel ant colony for nonlinear function optimization with graphics hardware acceleration, Proceedings of the 2009 IEEE international conference on systems, man and cybernetics, 1803-1808 (2009)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.