InterCriteria Analyzis of Hybrid Ant Colony Optimization Algorithm for Multiple Knapsack Problem

The local search procedure is a method for hybridization and improvement of the main algorithm, when complex problems are solved. It helps to avoid local optimums and to find faster the global one. In this paper we apply InterCriteria analysis (ICrA) on hybrid Ant Colony Optimization (ACO) algorithm for Multiple Knapsack Problem (MKP). The aim is to study the algorithm behavior comparing with traditional ACO algorithm. Based on the obtained numerical results and on the ICrA approach the efficiency and effectiveness of the proposed local search procedure are confirmed.

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1. The development of the proposed hybrid ACO algorithm with local search procedure has been funded by the Grant DFNI DN 12/5 and Grant No BG05M2OP001-1.001-0003, f inanced by the Science and Education for Smart Growth Operational Program and co-financed by the European Union through the European structural and Investment funds. The study of ACO algorithms behavior based on ICrA approach has been funded by the Grant KP-06-N22/1.

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2. Track 1: Artificial Intelligence in Applications

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3. Session: 14th International Workshop on Computational Optimization