A biased random-key genetic algorithm for the project scheduling problem with flexible resources

Bernardo F. Almeida (), Isabel Correia and Francisco Saldanha-da-Gama
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Bernardo F. Almeida: Universidade de Lisboa
Isabel Correia: Universidade Nova de Lisboa
Francisco Saldanha-da-Gama: Universidade de Lisboa

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2018, vol. 26, issue 2, No 8, 283-308

Abstract: Abstract In this paper, we investigate a resource-constrained project scheduling problem with flexible resources. This is an $$\mathcal {NP}$$ NP -hard combinatorial optimization problem that consists of scheduling a set of activities requiring specific resource units of several skills. The goal is to minimize the makespan of the project. We propose a biased random-key genetic algorithm for computing feasible solutions for the referred problem. We study different decoding mechanisms: an already existing method in the literature, a new adapted serial scheduling generation scheme, and a combination of both. The new procedure is tested using a set of benchmark instances of the problem. The results provide strong evidence that the new heuristic is robust and yields high-quality feasible solutions.

Keywords: Resource-constrained project scheduling; Flexible resources; Biased random-key genetic algorithm; 90B35 (Scheduling theory; deterministic); 90C59 (Approximation methods and heuristics) (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11750-018-0472-9

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