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Solving multi-objective production scheduling problems using metaheuristics. (English) Zbl 1065.90040
Summary: Most of research in production scheduling is concerned with the optimization of a single criterion. However the analysis of the performance of a schedule often involves more than one aspect and therefore requires a multi-objective treatment. In this paper we first present (Section 1) the general context of multi-objective production scheduling, analyze briefly the different possible approaches and define the aim of this study i.e. to design a general method able to approximate the set of all the efficient schedules for a large set of scheduling models. Then we introduce (Section 2) the models we want to treat–one machine, parallel machines and permutation flow shops – and the corresponding notations. The method used-called multi-objective simulated annealing – is described in Section 3. Section 4 is devoted to extensive numerical experiments and their analysis. Conclusions and further directions of research are discussed in the last section.

90B35 Deterministic scheduling theory in operations research
90B30 Production models
90C29 Multi-objective and goal programming
Full Text: DOI
[1] Chen, C.L.; Bulfin, R.L., Complexity of a single machine multi-criteria scheduling problems, European journal of operational research, 70, 115-125, (1993) · Zbl 0795.90032
[2] Crauwels, H.A.J.; Potts, C.N.; Van Wassenhove, L.N., Local search heuristics for the single machine total weighted tardiness scheduling problems, INFORMS, journal on computing, 10, 341-350, (1998) · Zbl 1092.90516
[3] Ehrgott, M.; Gandibleux, X., A survey and annotated bibliography of multiobjective combinatorial optimization, OR spektrum, 22, 425-460, (2000) · Zbl 1017.90096
[4] French, S., Sequencing and scheduling: an introduction to the mathematics of job shop, (1982), John Wiley & Sons · Zbl 0479.90037
[5] Ho, J.C.; Chang, Y.L., A new heuristic for n-job, m-shop problem, European journal of operations research, 52, 194-202, (1991) · Zbl 0725.90045
[6] H. Hoogeveen, Single machine bicriteria scheduling. Ph.D. dissertation, University of Eindhoven, 1992 · Zbl 0749.90042
[7] M.M. Koksalan, M. Azizoglu, S.K. Kondakci, Heuristics to minimize flowtime and maximum tardiness on a single machine, CMME Working paper series 9, Krannert School of Management, Perdue University, 1996 · Zbl 0858.90077
[8] Liao, Ch.J.; Yu, W.C.; Joe, C.B., Bicriteria scheduling in the two machines flow shop, Journal of operational research society, 48, 929-935, (1997) · Zbl 0892.90106
[9] T. Loukil, J. Teghem, Multicriteria scheduling problems. A survey. Submitted for publication · Zbl 0992.90074
[10] T. Loukil, Ordonnancement de production multicritère. Ph.D. thesis, Faculté des Sciences Economiques, Université de Sfax, Tunisie, 2000
[11] Loukil, T.; Teghem, J.; Fortemps, Ph., Solving multi-objective production scheduling problems with tabu-search, Control and cybernetics, 29, 3, (2000) · Zbl 0992.90074
[12] Nelson, R.T.; Sarin, R.K.; Daniels, R.L., Scheduling with multiple performances measures: the one machine case, Management science, 2, 464-479, (1986) · Zbl 0603.90070
[13] Neppalli, V.R.; Chen, Ch.L.; Gupta, J.N.D., Genetic algorithms for the two-stage bicriteria flow shop problem, European journal of operational research, 95, 356-373, (1996) · Zbl 0943.90584
[14] M. Pirlot, J. Teghem, Optimisation approchée en Recherche Opérationnelle: Recherches locales, réseaux neuronaux et satisfaction de contraintes, Collection IC^{2}, Hermès, 2002
[15] Rajendran, Ch., Two stage owshop scheduling problem with bicriteria, Journal of operational research society, 43, 9, 871-884, (1992) · Zbl 0757.90037
[16] Rajendran, Ch., Heuristics for scheduling in a flow shop with multiple objectives, European journal of operational research, 82, 540-555, (1995) · Zbl 0905.90107
[17] Selen, W.J.; Hott, D., A mixed integer goal programming formulation of the standard flow shop scheduling problem, Journal of operational research society, 37, 12, 1121-1126, (1986) · Zbl 0646.90041
[18] Shanthikumar, J.G., Scheduling n jobs on one machine to minimize the maximum tardiness with minimum number tardy jobs, Computers and operations research, 10, 3, 255-266, (1983)
[19] Taillard, E., Benchmarks for basic scheduling problems, European journal of operational research, 64, 278-285, (1995) · Zbl 0769.90052
[20] Teghem, J.; Tuyttens, D.; Ulungu, E.L., An interactive heuristic method for multiobjective combinatorial optimization, Computers and operations research, 27, 621-634, (2000) · Zbl 0961.90104
[21] Van Wassenhove; Gelders, L.F., Solving a bicriterion scheduling problem, European journal of operational research, 4, 42-48, (1980) · Zbl 0418.90054
[22] Ulungu, E.L.; Teghem, J.; Fortemps, Heuristic for multi-objective combinatorial optimization problems by simulated annealing, (), 229-238
[23] Ulungu, E.L.; Teghem, J.; Fortemps, Ph.; Tuyttens, D., MOSA method: A tool for solving MOCO problems, Journal of multi-criteria decision analysis, 8, 221-236, (1999) · Zbl 0935.90034
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