Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10696-011-9133-0
Title: New meta-heuristics for the resource-constrained project scheduling problem
Authors: Lim, A.
Ma, H.
Rodrigues, B.
Tan, S.T. 
Xiao, F.
Keywords: Genetic algorithms
Meta-heuristics
Resource-constrained project scheduling problem
Issue Date: 2013
Citation: Lim, A., Ma, H., Rodrigues, B., Tan, S.T., Xiao, F. (2013). New meta-heuristics for the resource-constrained project scheduling problem. Flexible Services and Manufacturing Journal 25 (1-2) : 48-73. ScholarBank@NUS Repository. https://doi.org/10.1007/s10696-011-9133-0
Abstract: In this paper, we study the resource-constrained project scheduling problem and introduce an annealing-like search heuristic which simulates the cooling process of a gas into a highly-ordered crystal. To achieve this, we develop diversification procedures that simulate the motion of high energy molecules as well as a local refinement procedure that simulates the motion of low energy molecules. We further improve the heuristic by incorporating a genetic algorithm framework. The meta-heuristic algorithms are applied to Kolisch's PSPLIB J30, J60 and J120 RCPSP instances. Experimental results show that they are effective and are among the best performing algorithms for the RCPSP. © 2012 Springer Science+Business Media, LLC.
Source Title: Flexible Services and Manufacturing Journal
URI: http://scholarbank.nus.edu.sg/handle/10635/39190
ISSN: 19366582
DOI: 10.1007/s10696-011-9133-0
Appears in Collections:Staff Publications

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