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

Abstract

In this paper, we investigate a resource-constrained project scheduling problem with flexible resources. This is an \(\mathcal {NP}\)-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.

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Notes

  1. 1.

    The percentage gaps are computed as explained in Sect. 4.2, with the lower bound for each instance being equal to the length of the corresponding critical path.

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Acknowledgements

This work was supported by National Funding from FCT—Fundação para a Ciência e a Tecnologia, under the projects Fundação para a Ciência e a Tecnologia, UID/MAT/04561/2013 (CMAF-CIO/FCUL) and UID/MAT/00297/2013 (CMA/FCT/UNL). The authors wish to thank the three anonymous referees for the valuable comments and suggestions provided which helped improving the manuscript.

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Correspondence to Bernardo F. Almeida.

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Almeida, B.F., Correia, I. & Saldanha-da-Gama, F. A biased random-key genetic algorithm for the project scheduling problem with flexible resources. TOP 26, 283–308 (2018). https://doi.org/10.1007/s11750-018-0472-9

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Keywords

  • Resource-constrained project scheduling
  • Flexible resources
  • Biased random-key genetic algorithm

Mathematics Subject Classification

  • 90B35 (Scheduling theory, deterministic)
  • 90C59 (Approximation methods and heuristics)