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A Genetic Algorithm for the Multi-Mode Resource-Constrained Project Scheduling Problem

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  • V. VAN PETEGHEM
  • M. VANHOUCKE

Abstract

In this paper we present a genetic algorithm for the multi-mode resource-constrained project scheduling problem (MRCPSP), in which multiple execution modes are available for each of the activities of the project. In contrast to a conventional genetic algorithm, we apply a bi-population genetic algorithm, which makes use of two seperate populations. We extend the serial schedule generation scheme by introducing a mode optimization procedure.We present detailed comparative computational results, which reveals that our procedure is among the most competitive algorithms for the MRCPSP.

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  • V. Van Peteghem & M. Vanhoucke, 2008. "A Genetic Algorithm for the Multi-Mode Resource-Constrained Project Scheduling Problem," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 08/494, Ghent University, Faculty of Economics and Business Administration.
    • Handle: RePEc:rug:rugwps:08/494
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    References listed on IDEAS

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    Cited by:

    1. V. Van Peteghem & M. Vanhoucke, 2009. "Using Resource Scarceness Characteristics to Solve the Multi-Mode Resource-Constrained Project Scheduling Problem," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/595, Ghent University, Faculty of Economics and Business Administration.
    2. Dayal Madhukar & Verma, Sanjay, 2015. "Multi-processor Exact Procedures for Regular Measures of the Multi-mode RCPSP," IIMA Working Papers WP2015-03-25, Indian Institute of Management Ahmedabad, Research and Publication Department.
    3. Dayal Madhukar & Verma, Sanjay, 2014. "Breadth-first and Best-first Exact Procedures for Regular Measures of the Multi-mode RCPSP," IIMA Working Papers WP2014-10-04, Indian Institute of Management Ahmedabad, Research and Publication Department.

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    Keywords

    project scheduling; genetic algorithm; multi-mode RCPSP;
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