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A Hybrid Scatter Search / Electromagnetism Meta-Heuristic for Project Scheduling

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  • D. DEBELS

    ()

  • B. DE REYCK
  • R. LEUS
  • M. VANHOUCKE

    ()

Abstract

In the last few decades, several effective algorithms for solving the resource-constrained project scheduling problem have been proposed. However, the challenging nature of this problem, summarised in its strongly NP-hard status, restricts the effectiveness of exact optimisation to relatively small instances. In this paper, we present a new meta-heuristic for this problem, able to provide near-optimal heuristic solutions. The procedure combines elements from scatter search, a generic population-based evolutionary search method, and a recently introduced heuristic method for the optimisation of unconstrained continuous functions based on an analogy with electromagnetism theory, hereafter referred to as the electromagnetism meta-heuristic. We present computational experiments on standard benchmark datasets, compare the results with current state-ofthe- art heuristics, and show that the procedure is capable of producing consistently good results for challenging instances of the resource-constrained project scheduling problem. We also demonstrate that the algorithm outperforms state-of-the-art existing heuristics.

Suggested Citation

  • D. Debels & B. De Reyck & R. Leus & M. Vanhoucke, 2004. "A Hybrid Scatter Search / Electromagnetism Meta-Heuristic for Project Scheduling," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/237, Ghent University, Faculty of Economics and Business Administration.
  • Handle: RePEc:rug:rugwps:04/237
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    References listed on IDEAS

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    Cited by:

    1. Naji-Azimi, Zahra & Toth, Paolo & Galli, Laura, 2010. "An electromagnetism metaheuristic for the unicost set covering problem," European Journal of Operational Research, Elsevier, vol. 205(2), pages 290-300, September.
    2. Elloumi, Sonda & Fortemps, Philippe, 2010. "A hybrid rank-based evolutionary algorithm applied to multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 205(1), pages 31-41, August.
    3. Ilkyeong Moon & Sanghyup Lee & Moonsoo Shin & Kwangyeol Ryu, 2016. "Evolutionary resource assignment for workload-based production scheduling," Journal of Intelligent Manufacturing, Springer, pages 375-388.
    4. Collewaert, V. & Manigart, S. & Rudy Aernoudt, 2007. "An assessment of government funding of business angel networks: a regional study," Vlerick Leuven Gent Management School Working Paper Series 2007-16, Vlerick Leuven Gent Management School.
    5. Kreter, Stefan & Rieck, Julia & Zimmermann, Jürgen, 2016. "Models and solution procedures for the resource-constrained project scheduling problem with general temporal constraints and calendars," European Journal of Operational Research, Elsevier, vol. 251(2), pages 387-403.
    6. Leyman, Pieter & Vanhoucke, Mario, 2017. "Capital- and resource-constrained project scheduling with net present value optimization," European Journal of Operational Research, Elsevier, vol. 256(3), pages 757-776.
    7. Mohammad Fathian & Javid Jouzdani & Mehdi Heydari & Ahmad Makui, 0. "Location and transportation planning in supply chains under uncertainty and congestion by using an improved electromagnetism-like algorithm," Journal of Intelligent Manufacturing, Springer, pages 1-18.
    8. Valls, Vicente & Ballestin, Francisco & Quintanilla, Sacramento, 2008. "A hybrid genetic algorithm for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 185(2), pages 495-508, March.
    9. Xiao, Jing & Wu, Zhou & Hong, Xi-Xi & Tang, Jian-Chao & Tang, Yong, 2016. "Integration of electromagnetism with multi-objective evolutionary algorithms for RCPSP," European Journal of Operational Research, Elsevier, vol. 251(1), pages 22-35.

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    Keywords

    project scheduling; heuristics; scatter search; electromagnetism;

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