Abstract
This paper describes the application of evolutionary algorithms to a typical multi-objective problem of serial production systems, in which two consecutive departments must organize their internal work, each taking into account the requirements of the other department. In particular, the paper compares three approaches based on different combinations of multi-objective evolutionary algorithms and local-search heuristics, using both small-size test instances and larger problems derived from an industrial production process. The analysis of the case-studies confirms the effectiveness of the evolutionary approaches, also enlightening the advantages and shortcomings of each considered algorithm.
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References
Aarts, E.H.L. and J.K. Lenstra (Eds.). (1997). Local Search in Combinatorial Optimization, Wiley.
Agnetis, A., P. Detti, C. Meloni, and D. Pacciarelli. (2001). “Setup Coordination Between Two Stages of a Supply Chain.” Annals of Operations Research, 107, 15–32.
Al-Haboubi, M.H. and S.Z. Selim. (1993). “A Sequencing Problem in the Weaving Industry.” European Journal of Operational Research, 66, 65–71.
Calegari, P., G. Coray, A. Hertz, d. Kobler, and P. Kuonen. (1999). “A Taxonomy of Evolutionary Algorithms in Combinatorial Optimization.” Journal of Heuristics, 5, 145–158.
Deb, K., A. Pratap, S. Agarwal, and T. Meyarivan. (2002). “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II.” IEEE Transactions on Evolutionary Computation, 6(2), 182–197.
Dimopoulos, C. and A.M.S. Zalzala. (2000). “Recent Developments in Evolutionary Computation for Manufacturing Optimisation: Problems, Solutions, and Comparisons.” IEEE Transactions on Evolutionary Computation, 4(2), 93–113.
Fanti, M.P., B. Maione, G. Piscitelli, and B. Turchiano. (1996). “Heuristic Scheduling of Jobs on a Multi-Product Batch Processing Machine.” International Journal of Production Research, 34(8), 2163–2186.
Fonseca, C.M. and P.J. Fleming (1995). “An Overview of Evolutionary Algorithms in Multi-Objective Optimization.” Evolutionary Computation, 3(1), 1–16.
Fonseca, C.M. and P.J. Fleming (1998). “Multiobjective Optimization and Multiple Constraint Handling with Evolutionary Algorithms—Part I: A Unified Formulation.” IEEE Transactions on Systems, Man and Cybernetics, Part A, 28(1), 26–37.
Gao, Y. and L.P. Shi. (2000). “Study on Multi-Objective Genetic Algorithm.” Proceedings of the 3rd World Congress on Intelligent Control and Automation, 1, 646–650.
Hertz, A., and D. Kobler. (2000). “A Framework for the Description of Evolutionary Algorithms.” European Journal of Operational Research, 126, 1–12.
Ishibuchi, H. and T. Murata. (1998). “A Multi-Objective Genetic Local Search Algorithm and its Application to Flowshop Scheduling.” IEEE Transactions on Systems, Man and Cybernetics, Part C, 28(3), 392–403.
Ishibuchi, H. and T. Murata. (1999). “Local Search Procedures in a Multi-Objective Genetic Local Search Algorithm for Scheduling Problems.” IEEE SMC ’99, International Conference on Systems, Man, and Cybernetics, 1, 665 –670.
Ishibuchi, H., T. Yoshida, T. Murata. (2002). “Selection of Initial Solutions for Local Search in Multiobjective Genetic Local Search.” IEEE CEC ’02, Proceedings of the 2002 Congress on Evolutionary Computation, 1, 950–955.
Ishibuchi H., T. Yoshida, and T. Murata. (2003). “Balance Between Genetic Search and Local Search in Memetic Algorithms for Multiobjective Permutation Flowshop Scheduling.” IEEE Transactions on Evolutionary Computation, 7(2), 204–223.
Kazarlis, S.A., S.E. Papadakis, J.B. Theocharis, and V. Petridis. (2001). “Microgenetic Algorithms as Generalized Hill-Climbing Operators for GA Optimization.” IEEE Transactions on Evolutionary Computation, 5(3), 204–217.
Knowles, J. and D. Corne. (1999). “The Pareto Archived Evolution Strategy: A New Baseline Algorithm for Multiobjective Optimization.” IEEE CEC 99, Proceedings of the 1999 Congress on Evolutionary Computation, 1, 98–105.
Landa Silva, J.D. and E.K. Burke. (2004). “A Tutorial on Multiobjective Metaheuristics for Scheduling and Timetabling.” In X. Gandibleux, M. Sevaux, K. Sorensen, and V.T’ kindt (Eds.), Multiple Objective Meta-Heuristics, Lecture Notes in Economics and Mathematical Systems. Berlin: Springer.
Meloni, C. (2001). “An Evolutionary Algorithm for the Sequence Coordination in Furniture Production.” Lecture Notes of Computer Science, 2264, 91–106.
Meloni, C., D. Naso, and B. Turchiano. (2003). “Multi-Objective Genetics Algorithms for a Class of Sequencing Problems in Manufacturing Environments.” 2003 IEEE International Conference on Systems, Man & Cybernetics, October 5–8, 2003, Washington, D.C.
Michalewicz, Z. (1996). Genetic Algorithms + Data Structures = Evolution Programs, Berlin: Springer.
Murata, T., H. Ishibuchi, and H. Tanaka. (1996). “Genetic Algorithms for Flowshop Scheduling Problems.” Computers and Industrial Engineering, 30(4), 1061–1071.
Naso, D., B. Turchiano, and C. Meloni. (2004). “Single and Multi-Objective Evolutionary Algorithms for the Coordination of Serial Manufacturing Operations.” Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Technical Report.
Reeves, C.R. (1995). “A Genetic Algorithm for Flowshop Sequencing.” Computers And Operations Research, 22, 5–13.
Spina, R., L.M. Galantucci, and M. Dassisti. (2003). “A Hybrid Approach to the Single Line Scheduling Problem with Multiple Products and Sequence-Dependent Time.” Computers & Industrial Engineering, 45, 573–583.
Srinvas, N. and K. Deb. (1995). “Multiobjective Function Optimization using Nondominated Sorting Genetic Algorithms.” Evolutionary Computation Journal, 2(3), 221–248.
T’kindt, V. and J.-C. Billaut. (2002). Multicriteria Scheduling—Theory, Models and Algorithms. Berlin: Springer.
Van Veldhuizen, D.A. and G.B. Lamont. (2000) “On Measuring Multiobjective Evolutionary Algorithm Performance.” IEEE CEC00, Proceedings of the 2000 Congress on Evolutionary Computation, pp. 204–211.
Voss, S., S. Martello, I.H. Osman, and C. Roucariol. (Eds). (1999). Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization. Kluwer.
Zitzler, E. (1999). “Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications,” Doctoral Dissertation ETH 13398, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland.
Zitzler, E., K. Deb, and L. Thiele. (2000). “Comparison of Multiobjective Evolutionary Algorithms: Empirical Results.” Evolutionary Computation, 8(2), 173–195.
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Meloni, C., Naso, D. & Turchiano, B. Setup coordination between two stages of a production system: A multi-objective evolutionary approach. Ann Oper Res 147, 175–198 (2006). https://doi.org/10.1007/s10479-006-0065-0
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DOI: https://doi.org/10.1007/s10479-006-0065-0