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Estimation of distribution algorithms for the multi-mode resource constrained project scheduling problem.

Ayodele, Mayowa; McCall, John; Regnier-Coudert, Olivier

Authors

Mayowa Ayodele

John McCall

Olivier Regnier-Coudert

Abstract

Multi-Mode Resource Constrained Project Problem (MRCPSP) is a multi-component problem which combines two interacting sub-problems; activity scheduling and mode assignment. Multi-component problems have been of research interest to the evolutionary computation community as they are more complex to solve. Estimation of Distribution Algorithms (EDAs) generate solutions by sampling a probabilistic model that captures key features of good solutions. Often they can significantly improve search efficiency and solution quality. Previous research has shown that the mode assignment sub-problem can be more effectively solved with an EDA. Also, a competitive Random Key based EDA (RK-EDA) for permutation problems has recently been proposed. In this paper, activity and mode solutions are respectively generated using the RK-EDA and an integer based EDA. This approach is competitive with leading approaches of solving the MRCPSP.

Start Date Jun 5, 2017
Publication Date Jul 7, 2017
Publisher Institute of Electrical and Electronics Engineers
Article Number 7969491
Pages 1579-1586
Institution Citation AYODELE, M., MCCALL, J. and REGNIER-COUDERT, O. 2017. Estimation of distribution algorithms for the multi-mode resource constrained project scheduling problem. In Proceedings of the 2017 IEEE congress on evolutionary computation (CEC 2017), 5-8 June 2017, San Sebastian, Spain. New York: IEEE [online], article number 7969491, pages 1579-1586. Available from: https://doi.org/10.1109/CEC.2017.7969491
DOI https://doi.org/10.1109/CEC.2017.7969491
Keywords Multicomponent problems; Activity scheduling; Mode assignment; Multimode resource constrained projecte problem (MRCPSP)

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