Abstract
This paper presents a comparative study of multi-objective evolutionary algorithms on the bi-objective 2-dimensional vector packing problem. Three state-of-the-art methods which prove their efficiency for a large variety of multi-objective optimization problems were designed to approximate the whole Pareto set of the problem. Computational experiments are performed on well-known benchmark test instances. The proposed algorithms are extensively compared to each other using different performance metrics.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ajiro, Y., Tanaka, A.: Improving packing algorithms for server consolidation. In: International CMG Conference, pp. 399–406. Computer Measurement Group (2007)
Bleuler, S., Laumanns, M., Thiele, L., Zitzler, E.: Pisa: A platform and programming language independent interface for search algorithm. In: Fonseca, C.M., Fleming, P.J., Zitzler, E., Deb, K., Thiele, L. (eds.) EMO 2003. LNCS, vol. 2632, pp. 494–508. Springer, Heidelberg (2003)
Caprara, A., Toth, P.: Lower bounds and algorithms for the 2-dimensional vector packing problem. Discrete Applied Mathematics 111(3), 231–262 (2001)
Coffman, J.E.G., Garey, M.R., Johnson, D.S.: Approximation algorithms for bin packing: a survey, pp. 46–93 (1997)
Dahmani, N., Clautiaux, F., Krichen, S., Talbi, E.-G.: Iterative approaches for solving a multi-objective 2-dimensional vector packing problem. Computers & Industrial Engineering (2013), http://dx.doi.org/10.1016/j.cie.2013.05.016
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast elitist multi-objective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6, 182–197 (2000)
Eilon, S., Christofides, N.: The loading problem. Management Science 17, 259–267 (1971)
Ishibuchi, H., Murata, T.: Multi-objective genetic local search algorithm and its application to flowshop scheduling. IEEE Transactions on Systems, Man and Cybernetics 28(3), 392–403 (1998)
Knowles, J., Thiele, L., Zitzler, E.: A Tutorial on the Performance Assessment of Stochastic Multiobjective Optimizers. TIK Report 214, Computer Engineering and Networks Laboratory (TIK), ETH Zurich (2006)
Liefooghe, A., Basseur, M., Jourdan, L., Talbi, E.-G.: ParadisEO-MOEO: A framework for evolutionary multi-objective optimization. In: Obayashi, S., Deb, K., Poloni, C., Hiroyasu, T., Murata, T. (eds.) EMO 2007. LNCS, vol. 4403, pp. 386–400. Springer, Heidelberg (2007)
Spieksma, F.C.R.: A branch-and-bound algorithm for the two-dimensional vector packing problem. Computers & Operations Research 21, 19–25 (1994)
Zitzler, E., Künzli, S.: Indicator-based selection in multiobjective search. In: Yao, X., Burke, E.K., Lozano, J.A., Smith, J., Merelo-Guervós, J.J., Bullinaria, J.A., Rowe, J.E., Tiňo, P., Kabán, A., Schwefel, H.-P. (eds.) PPSN 2004. LNCS, vol. 3242, pp. 832–842. Springer, Heidelberg (2004)
Zitzler, E., Laumanns, M., Thiele, L.: SPEA2: Improving the strength pareto evolutionary algorithm for multiobjective optimization. In: Giannakoglou, K.C., Tsahalis, D.T., Périaux, J., Papailiou, K.D., Fogarty, T. (eds.) Evolutionary Methods for Design Optimization and Control with Applications to Industrial Problems, Athens, Greece, pp. 95–100. International Center for Numerical Methods in Engineering (2001)
Zitzler, E., Thiele, L.: Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach. IEEE Transactions on Evolutionary Computation 3(4), 257–271 (1999)
Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C.M., da Fonseca, V.G.: Performance assessment of multiobjective optimizers: An analysis and review. IEEE Transactions on Evolutionary Computation 7, 117–132 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Dahmani, N., Krichen, S., Clautiaux, F., Talbi, EG. (2013). A Comparative Study of Multi-objective Evolutionary Algorithms for the Bi-objective 2-Dimensional Vector Packing Problem. In: Widmayer, P., Xu, Y., Zhu, B. (eds) Combinatorial Optimization and Applications. COCOA 2013. Lecture Notes in Computer Science, vol 8287. Springer, Cham. https://doi.org/10.1007/978-3-319-03780-6_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-03780-6_4
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03779-0
Online ISBN: 978-3-319-03780-6
eBook Packages: Computer ScienceComputer Science (R0)