A new hybrid algorithm for the multidimensional knapsack problem

Authors:
Xiaoxia Zhang;Zhe Liu;Qiuying Bai
Affiliations:
College of Software Engineering, University of Science and Technology, Liaoning, China;College of Software Engineering, University of Science and Technology, Liaoning, China;College of Software Engineering, University of Science and Technology, Liaoning, China
Venue:
ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
Year:
2011

Citing 2
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Abstract

This paper presents a novel hybrid algorithm to solve the multidimensional knapsack problem. The main feature of this hybrid algorithm is to combine the solution construction mechanism of ant colony optimization (ACO) into scatter search (SS). It considers both solution quality and diversification. A new mechanism of the subset combination method has been applied simultaneity, which hybridizes mechanism of the pheromone trail updating with combination mechanism of scatter search to generate new solutions. Second, an improvement algorithm should be embedded into the scatter search framework to improve solutions. Finally, the experimental results have shown that our proposed method is competitive to solve the multidimensional knapsack problem compared with the other heuristic methods in terms of solution quality.