A genetic algorithm to solve the multidimensional Knapsack problem

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BERBERLER M. E., Guler A., NURİYEV U.

Mathematical and Computational Applications, vol.18, no.3, pp.486-494, 2013 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 18 Issue: 3
  • Publication Date: 2013
  • Doi Number: 10.3390/mca18030486
  • Journal Name: Mathematical and Computational Applications
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.486-494
  • Keywords: Evolutionary algorithms, Genetic algorithm, Heuristic approach, Multidimensional Knapsack problem
  • Dokuz Eylül University Affiliated: Yes

Abstract

In this paper, The Multidimensional Knapsack Problem (MKP) which occurs in many different applications is studied and a genetic algorithm to solve the MKP is proposed. Unlike the technique of the classical genetic algorithm, initial population is not randomly generated in the proposed algorithm, thus the solution space is scanned more efficiently. Moreover, the algorithm is written in C programming language and is tested on randomly generated instances. It is seen that the algorithm yields optimal solutions for all instances.