Abstract
In this paper, we describe two new improvements of the well known Martello and Toth Heuristic Method (MTHM). Our new improvements are very simple and at the same time they are very efficient since they yield to more than 15% over MTHM with an excellent execution time performance in relatively large problem instances. Further, the new improvements give a very close results to sophisticated meta-heuristics namely Genetic Algorithms with a gap less than 1% within a time slot less than a second.
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
Martello, S., Toth, P.: Heuristic algorithms for the multiple knapsack problem. Computing 27, 93–112 (1981)
Fukunaga, A.: A new grouping genetic algorithm for the multiple knapsack problem. In: Proc. IEEE Congress on Evolutionary Computation, pp. 2225–2232 (2008)
Fukunaga, A., Tazoe, S.: Combining Multiple Representations in a Genetic Algorithm for the Multiple Knapsack Problem. In: Proc of the 11th IEEE Congress on Evolutionary Computation, pp. 2423–2430 (2009)
Raidl, R.: The multiple container packing problem: A genetic algorithm approach with weighted codings. ACM SIGAPP Applied Computing Review, 22–31 (1999)
Falkenauer, E.: A hybrid grouping genetic algorithm for bin packing. Journal of Heuristics 2, 5–30 (1996)
Pisinger, D.: An exact algorithm for large multiple knapsack problems. European Journal of Operational Research 114, 528–541 (1999)
Fukunaga, A.: A branch-and-bound algorithm for hard multiple knapsack problems. Annals of Operations Research 184(1), 97–119 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Laalaoui, Y. (2013). Improved Swap Heuristic for the Multiple Knapsack Problem. In: Rojas, I., Joya, G., Gabestany, J. (eds) Advances in Computational Intelligence. IWANN 2013. Lecture Notes in Computer Science, vol 7902. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38679-4_55
Download citation
DOI: https://doi.org/10.1007/978-3-642-38679-4_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38678-7
Online ISBN: 978-3-642-38679-4
eBook Packages: Computer ScienceComputer Science (R0)