An efficient hybrid genetic algorithm for scheduling projects with resource constraints and multiple execution modes

Antonio Lova, Pilar Tormos, Mariamar Cervantes and Federico Barber

International Journal of Production Economics, 2009, vol. 117, issue 2, 302-316

Abstract: Multi-mode Resource Constrained Project Scheduling Problem (MRCPSP) aims at finding the start times and execution modes for the activities of a project that optimize a given objective function while verifying a set of precedence and resource constraints. In this paper, we focus on this problem and develop a hybrid Genetic Algorithm (MM-HGA) to solve it. Its main contributions are the mode assignment procedure, the fitness function and the use of a very efficient improving method. Its performance is demonstrated by extensive computational results obtained on a set of standard instances and against the best currently available algorithms.

Keywords: Project; management; and; scheduling; Renewable; and; non-renewable; resources; Genetic; Algorithms; Multimode; forward-backward; improving; method (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (25)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:117:y:2009:i:2:p:302-316

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