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On implementation of local search and genetic algorithm techniques for some combinatorial optimization problems

Anton Bondarenko (anton.bondarenko***at***gmail.com)

Abstract: In this paper we propose the approach to solving several combinatorial optimization problems using local search and genetic algorithm techniques. Initially this approach was developed in purpose to overcome some difficulties inhibiting the application of above-mentioned techniques to the problems of the Questionnaire Theory. But when the algorithms were developed it became clear that them could be successfully applied also to the Minimal Set Cover, the 0-1-Knapsack and probably to other combinatorial optimization problems.

Keywords: Binary Questionnaire, Minimal Set Cover, Weighted Set Cover, 0-1-Knapsack, Local Search, Genetic Algorithm

Category 1: Combinatorial Optimization (Meta Heuristics )

Category 2: Combinatorial Optimization (Approximation Algorithms )

Category 3: Combinatorial Optimization (Other )

Citation: Arxiv.org: http://arxiv.org/abs/1004.5262

Download: [PDF]

Entry Submitted: 04/12/2011
Entry Accepted: 04/13/2011
Entry Last Modified: 04/13/2011

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