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Multi-project scheduling with two-stage decomposition

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  • Anıl Can
  • Gündüz Ulusoy

Abstract

We consider a non-preemptive, zero time lag multi-project scheduling problem with multiple modes and limited renewable and nonrenewable resources. A two-stage decomposition approach is adopted to formulate the problem as a hierarchy of 0-1 mathematical programming models. In stage one; each project is reduced to a macro-activity with macro-modes. The macro-activities are combined into a single macro-activity network over which the macro-activity scheduling problem (MP) is defined, where the objective is the maximization of the net present value with positive cash flows and the renewable resource requirements are time-dependent. An exact solution procedure and a genetic algorithm (GA) approach are proposed for solving the MP. A GA is also employed to generate an initial solution for the exact solution procedure. The first stage terminates with a post-processing procedure to distribute the remaining resource capacities. Using the start times and the resource profiles obtained in stage one, each project is scheduled in stage two for minimum makespan. Three new test problem sets are generated with 81, 84 and 27 problems each, and three different configurations of solution procedures are tested. Copyright Springer Science+Business Media New York 2014

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  • Anıl Can & Gündüz Ulusoy, 2014. "Multi-project scheduling with two-stage decomposition," Annals of Operations Research, Springer, vol. 217(1), pages 95-116, June.
    • Handle: RePEc:spr:annopr:v:217:y:2014:i:1:p:95-116:10.1007/s10479-014-1555-0
    DOI: 10.1007/s10479-014-1555-0
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    Cited by:

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    2. Yukang He & Tao Jia & Weibo Zheng, 2024. "Simulated annealing for centralised resource-constrained multiproject scheduling to minimise the maximal cash flow gap under different payment patterns," Annals of Operations Research, Springer, vol. 338(1), pages 115-149, July.
    3. Ghazaleh Ahmadi & Reza Tavakkoli-Moghaddam & Armand Baboli & Mehdi Najafi, 2022. "A decision support model for robust allocation and routing of search and rescue resources after earthquake: a case study," Operational Research, Springer, vol. 22(2), pages 1039-1081, April.
    4. Bredael, Dries & Vanhoucke, Mario, 2023. "Multi-project scheduling: A benchmark analysis of metaheuristic algorithms on various optimisation criteria and due dates," European Journal of Operational Research, Elsevier, vol. 308(1), pages 54-75.
    5. Feifei Li & Zhe Xu, 2018. "A multi-agent system for distributed multi-project scheduling with two-stage decomposition," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-24, October.
    6. Maryam Sadeghloo & Saeed Emami & Ali Divsalar, 2024. "A Benders decomposition algorithm for the multi-mode resource-constrained multi-project scheduling problem with uncertainty," Annals of Operations Research, Springer, vol. 339(3), pages 1637-1677, August.
    7. Gómez Sánchez, Mariam & Lalla-Ruiz, Eduardo & Fernández Gil, Alejandro & Castro, Carlos & Voß, Stefan, 2023. "Resource-constrained multi-project scheduling problem: A survey," European Journal of Operational Research, Elsevier, vol. 309(3), pages 958-976.
    8. Wuliang Peng & Jiali lin & Jingwen Zhang & Liangwei Chen, 2022. "A bi-objective hierarchical program scheduling problem and its solution based on NSGA-III," Annals of Operations Research, Springer, vol. 308(1), pages 389-414, January.
    9. Arda Turkgenci & Huseyin Guden & Mehmet Gülşen, 2021. "Decomposition based extended project scheduling for make-to-order production," Operational Research, Springer, vol. 21(2), pages 801-825, June.
    10. Sergey Kovalev, 2015. "Maximizing total tardiness on a single machine in $$O(n^2)$$ O ( n 2 ) time via a reduction to half-product minimization," Annals of Operations Research, Springer, vol. 235(1), pages 815-819, December.
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