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A Permutation-Based Bees Algorithm for Solving Resource-Constrained Project Scheduling Problem

A Permutation-Based Bees Algorithm for Solving Resource-Constrained Project Scheduling Problem

Mohamed Amine Nemmich, Fatima Debbat, Mohamed Slimane
Copyright: © 2019 |Volume: 10 |Issue: 4 |Pages: 24
ISSN: 1947-9263|EISSN: 1947-9271|EISBN13: 9781522566397|DOI: 10.4018/IJSIR.2019100101
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MLA

Nemmich, Mohamed Amine, et al. "A Permutation-Based Bees Algorithm for Solving Resource-Constrained Project Scheduling Problem." IJSIR vol.10, no.4 2019: pp.1-24. http://doi.org/10.4018/IJSIR.2019100101

APA

Nemmich, M. A., Debbat, F., & Slimane, M. (2019). A Permutation-Based Bees Algorithm for Solving Resource-Constrained Project Scheduling Problem. International Journal of Swarm Intelligence Research (IJSIR), 10(4), 1-24. http://doi.org/10.4018/IJSIR.2019100101

Chicago

Nemmich, Mohamed Amine, Fatima Debbat, and Mohamed Slimane. "A Permutation-Based Bees Algorithm for Solving Resource-Constrained Project Scheduling Problem," International Journal of Swarm Intelligence Research (IJSIR) 10, no.4: 1-24. http://doi.org/10.4018/IJSIR.2019100101

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Abstract

In this article, a novel Permutation-based Bees Algorithm (PBA) is proposed for the resource-constrained project scheduling problem (RCPSP) which is widely applied in advanced manufacturing, production planning, and project management. The PBA is a modification of existing Bees Algorithm (BA) adapted for solving combinatorial optimization problems by changing some of the algorithm's core concepts. The algorithm treats the solutions of RCPSP as bee swarms and employs the activity-list representation and moves operators for the bees, in association with the serial scheduling generation scheme (Serial SGS), to execute the intelligent updating process of the swarms to search for better solutions. The performance of the proposed approach is analysed across various problem complexities associated with J30, J60 and J120 full instance sets of PSPLIB and compared with other approaches from the literature. Simulation results demonstrate that the proposed PBA provides an effective and efficient approach for solving RCPSP.

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