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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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    Cited by:

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    3. Anurag Agarwal & Selcuk Colak & Jason Deane, 2010. "NeuroGenetic approach for combinatorial optimization: an exploratory analysis," Annals of Operations Research, Springer, vol. 174(1), pages 185-199, February.
    4. M. Vanhoucke, 2007. "A genetic algorithm to investigate the trade-off between project lead time and net present value," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/456, Ghent University, Faculty of Economics and Business Administration.
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    6. Xabier A. Martin & Rosa Herrero & Angel A. Juan & Javier Panadero, 2024. "An Agile Adaptive Biased-Randomized Discrete-Event Heuristic for the Resource-Constrained Project Scheduling Problem," Mathematics, MDPI, vol. 12(12), pages 1-21, June.
    7. 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.
    8. Kadri, Roubila Lilia & Boctor, Fayez F., 2018. "An efficient genetic algorithm to solve the resource-constrained project scheduling problem with transfer times: The single mode case," European Journal of Operational Research, Elsevier, vol. 265(2), pages 454-462.
    9. 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.
    10. Servranckx, Tom & Coelho, José & Vanhoucke, Mario, 2024. "A genetic algorithm for the Resource-Constrained Project Scheduling Problem with Alternative Subgraphs using a boolean satisfiability solver," European Journal of Operational Research, Elsevier, vol. 316(3), pages 815-827.
    11. Esmaeil Mehdizadeh & Mohammad Teimouri & Arash Zaretalab & S. T. A. Niaki, 2017. "A Combined Approach Based on K-Means and Modified Electromagnetism-Like Mechanism for Data Clustering," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 1279-1307, September.
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    13. Zhenyuan Liu & Lei Xiao & Jing Tian, 2016. "An activity-list-based nested partitions algorithm for resource-constrained project scheduling," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4744-4758, August.
    14. 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.
    15. Anurag Agarwal, 2009. "Theoretical insights into the augmented-neural-network approach for combinatorial optimization," Annals of Operations Research, Springer, vol. 168(1), pages 101-117, April.
    16. Coelho, José & Vanhoucke, Mario, 2011. "Multi-mode resource-constrained project scheduling using RCPSP and SAT solvers," European Journal of Operational Research, Elsevier, vol. 213(1), pages 73-82, August.
    17. 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.
    18. Ranjbar, Mohammad & De Reyck, Bert & Kianfar, Fereydoon, 2009. "A hybrid scatter search for the discrete time/resource trade-off problem in project scheduling," European Journal of Operational Research, Elsevier, vol. 193(1), pages 35-48, February.
    19. Luis F. Machado-Domínguez & Carlos D. Paternina-Arboleda & Jorge I. Vélez & Agustín Barrios-Sarmiento, 2022. "An adaptative bacterial foraging optimization algorithm for solving the MRCPSP with discounted cash flows," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 221-248, July.
    20. Len Vandenheede & Mario Vanhoucke & Broos Maenhout, 2016. "A scatter search for the extended resource renting problem," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4723-4743, August.
    21. Ilkyeong Moon & Sanghyup Lee & Moonsoo Shin & Kwangyeol Ryu, 2016. "Evolutionary resource assignment for workload-based production scheduling," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 375-388, April.
    22. Mohammad Fathian & Javid Jouzdani & Mehdi Heydari & Ahmad Makui, 2018. "Location and transportation planning in supply chains under uncertainty and congestion by using an improved electromagnetism-like algorithm," Journal of Intelligent Manufacturing, Springer, vol. 29(7), pages 1447-1464, October.
    23. Fekri, Roxana & Amiri, Maghsoud & Sajjad, Rasoul & Golestaneh, Ramin, 2016. "Optimization of Bank Portfolio Investment Decision Considering Resistive Economy," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 11(4), pages 375-400, October.
    24. Anupam Biswas & K. K. Mishra & Shailesh Tiwari & A. K. Misra, 2013. "Physics-Inspired Optimization Algorithms: A Survey," Journal of Optimization, Hindawi, vol. 2013, pages 1-16, June.

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