An Artificial Bee Colony Algorithm for the Quadratic Knapsack Problem

Authors:
Srikanth Pulikanti;Alok Singh
Affiliations:
Department of Computer and Information Sciences, University of Hyderabad, Hyderabad, India 500046;Department of Computer and Information Sciences, University of Hyderabad, Hyderabad, India 500046
Venue:
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Year:
2009

Citing 6
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Abstract

In this paper we have proposed a new hybrid approach combining artificial bee colony algorithm with a greedy heuristic and a local search for the quadratic knapsack problem. Quadratic knapsack problem belongs to traditional knapsack problem family and it is an extension of the well-known 0/1 knapsack problem. In this problem profits are also associated with pairs of objects along with individual objects. As this problem is an extension of the 0/1 knapsack problem, it is also $\mathcal{NP}$-Hard. Artificial bee colony algorithm is a new swarm intelligence technique inspired by foraging behavior of natural honey bee swarms. Performance of our algorithm on standard quadratic knapsack problem instances is compared with the other best heuristic techniques. Results obtained on these instances show that our hybrid artificial bee colony algorithm is superior to these techniques in many aspects.