An efficient hybrid genetic algorithm for scheduling projects with resource constraints and multiple execution modes
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.
Year of publication: |
2009
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Authors: | Lova, Antonio ; Tormos, Pilar ; Cervantes, Mariamar ; Barber, Federico |
Published in: |
International Journal of Production Economics. - Elsevier, ISSN 0925-5273. - Vol. 117.2009, 2, p. 302-316
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Publisher: |
Elsevier |
Keywords: | Project management and scheduling Renewable and non-renewable resources Genetic Algorithms Multimode forward-backward improving method |
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