A Bi-Population Based Genetic Algorithm for the Resource-Constrained Project Scheduling Problem

D. Debels () and Mario Vanhoucke

Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium from Ghent University, Faculty of Economics and Business Administration

Abstract: The resource-constrained project scheduling problem (RCPSP) is one of the most challenging problems in project scheduling. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions for more challenging problem instances. In this paper, we present a new genetic algorithm (GA) that, in contrast of a conventional GA, makes use of two separate populations. This bi-population genetic algorithm (BPGA) operates on both a population of left-justified schedules and a population of right-justified schedules in order to fully exploit the features of the iterative forward/backward local search scheduling technique. Comparative computational results reveal that this procedure can be considered as today’s best performing RCPSP heuristic.

Pages: 15 pages
Date: 2005-02
New Economics Papers: this item is included in nep-cmp
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Citations: View citations in EconPapers (4)

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Working Paper: A Bi-Population Based Genetic Algorithm for the Resource-Constrained Project Scheduling Problem (2005)
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Persistent link: https://EconPapers.repec.org/RePEc:rug:rugwps:05/294

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