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A Review and Comparison of Genetic Algorithms for the 0-1 Multidimensional Knapsack Problem

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  • Bernhard Lienland

    (University of Regensburg, Regensburg, Germany)

  • Li Zeng

    (University of Regensburg, Regensburg, Germany)

Abstract

The 0-1 multidimensional knapsack problem (MKP) is a well-known combinatorial optimization problem with several real-life applications, for example, in project selection. Genetic algorithms (GA) are effective heuristics for solving the 0-1 MKP. Multiple individual GAs with specific characteristics have been proposed in literature. However, so far, these approaches have only been partially compared in multiple studies with unequal conditions. Therefore, to identify the “best” genetic algorithm, this article reviews and compares 11 existing GAs. The authors' tests provide detailed information on the GAs themselves as well as their performance. The authors validated fitness values and required computation times in varying problem types and environments. Results demonstrate the superiority of one GA.

Suggested Citation

  • Bernhard Lienland & Li Zeng, 2015. "A Review and Comparison of Genetic Algorithms for the 0-1 Multidimensional Knapsack Problem," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 6(2), pages 21-31, April.
    • Handle: RePEc:igg:joris0:v:6:y:2015:i:2:p:21-31
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