An improved ant colony optimization algorithm for nonlinear resource-leveling problems. (English) Zbl 1219.90194

Summary: The notion of using a meta-heuristic approach to solve nonlinear resource-leveling problems has been intensively studied in recent years. Premature convergence and poor exploitation are the main obstacles for the heuristic algorithms. Analyzing the characteristics of the project topology network, this paper introduces a directional ant colony optimization (DACO) algorithm for solving nonlinear resource-leveling problems. The DACO algorithm introduced can efficiently improve the convergence rate and the quality of solution for real-project scheduling.


90C59 Approximation methods and heuristics in mathematical programming
Full Text: DOI


[1] Leu, S. S.; Yang, C. H.; Huang, J. C., Resource leveling in construction by genetic algorithm-based optimization and its decision support system application, Automation in Construction, 10, 27-41 (2000)
[2] Roca, J.; Pugnaghi, E.; Libert, G., Solving an extended resource leveling problem with multiobjective evolutionary algorithms, International Journal of Computational Intelligence, 4, 4, 289-300 (2008)
[4] Colorni, A.; Dorigo, M.; Maniezzo, V., Distributed optimization by ant colonies, (Proceedings of Ecal91—European Conference on Artificial Life, Paris, France (1991), Elsevier Publishing), 134-142
[5] Dorigo, M.; Gambardella, L. M., Ant colony system: a cooperative learning approach to the traveling salesman problems, IEEE Transactions on Evolutionary Computation, 1, 1, 53-66 (1997)
[6] Merkle, D.; Middendorf, M.; Schmeck, H., Ant colony optimization for resource-constrained project scheduling, IEEE Transactions on Evolutionary Computation, 6, 4, 333-346 (2002)
[7] Chen, W.; Shi, Y. J.; Teng, H. F.; Lan, X. P.; Hu, L. C., An efficient hybrid algorithm for resource-constrained project scheduling, Information Sciences, 180, 1031-1039 (2010)
[8] Bottee, H. M.; Bonabeau, E., Evolving ant colony optimization, Advances in Complex Systems, 1, 149-159 (1998)
[9] Michels, R.; Middendorf, M., An island model based ant system with lookahead for the shortest supersequence problem, (Eiben, A. E.; etal., PPSN V. PPSN V, LNCS, vol. 1498 (1998)), 692-701
[10] Duan, Q.; Liao, T. Warren, Improved ant colony optimization algorithms for determining project critical paths, Automation in Construction, 19, 6, 676-693 (2010)
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.