On Application of the Local Search and the Genetic Algorithms Techniques to Some Combinatorial Optimization Problems

TL;DR

This paper explores the application of local search and genetic algorithms to various combinatorial optimization problems, demonstrating their effectiveness beyond initial theoretical contexts, including set cover and knapsack problems.

Contribution

It introduces a novel approach combining local search and genetic algorithms for multiple combinatorial problems, expanding their practical applicability.

Findings

Successful application to Minimum Set Cover and 0-1 Knapsack problems

Algorithms overcome previous application difficulties

Potential for broader use in combinatorial optimization

Abstract

In this paper the approach to solving several combinatorial optimization problems using the local search and the genetic algorithm techniques is proposed. 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 Minimum Set Cover, the 0-1-Knapsack and probably to other combinatorial optimization problems.