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A genetic algorithm with neighborhood search for the resource‐constrained project scheduling problem

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  • Sepehr Proon
  • Mingzhou Jin

Abstract

The resource‐constrained project scheduling problem (RCPSP) consists of a set of non‐preemptive activities that follow precedence relationship and consume resources. Under the limited amount of the resources, the objective of RCPSP is to find a schedule of the activities to minimize the project makespan. This article presents a new genetic algorithm (GA) by incorporating a local search strategy in GA operators. The local search strategy improves the efficiency of searching the solution space while keeping the randomness of the GA approach. Extensive numerical experiments show that the proposed GA with neighborhood search works well regarding solution quality and computational time compared with existing algorithms in the RCPSP literature, especially for the instances with a large number of activities. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011

Suggested Citation

  • Sepehr Proon & Mingzhou Jin, 2011. "A genetic algorithm with neighborhood search for the resource‐constrained project scheduling problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(2), pages 73-82, March.
    • Handle: RePEc:wly:navres:v:58:y:2011:i:2:p:73-82
    DOI: 10.1002/nav.20439
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    1. Sönke Hartmann, 1998. "A competitive genetic algorithm for resource‐constrained project scheduling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 45(7), pages 733-750, October.
    2. Mireille Palpant & Christian Artigues & Philippe Michelon, 2004. "LSSPER: Solving the Resource-Constrained Project Scheduling Problem with Large Neighbourhood Search," Annals of Operations Research, Springer, vol. 131(1), pages 237-257, October.
    3. Klein, Robert, 1999. "Computing lower bounds by destructive improvement - an application to resource-constrained project scheduling," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 10913, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Rainer Kolisch & Arno Sprecher & Andreas Drexl, 1995. "Characterization and Generation of a General Class of Resource-Constrained Project Scheduling Problems," Management Science, INFORMS, vol. 41(10), pages 1693-1703, October.
    5. Kolisch, Rainer, 1996. "Serial and parallel resource-constrained project scheduling methods revisited: Theory and computation," European Journal of Operational Research, Elsevier, vol. 90(2), pages 320-333, April.
    6. Kolisch, R. & Padman, R., 2001. "An integrated survey of deterministic project scheduling," Omega, Elsevier, vol. 29(3), pages 249-272, June.
    7. Rainer Kolisch & Andreas Drexl, 1996. "Adaptive search for solving hard project scheduling problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 43(1), pages 23-40, February.
    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. Klein, Robert & Scholl, Armin, 1999. "Computing lower bounds by destructive improvement: An application to resource-constrained project scheduling," European Journal of Operational Research, Elsevier, vol. 112(2), pages 322-346, January.
    10. Valls, Vicente & Ballestin, Francisco & Quintanilla, Sacramento, 2005. "Justification and RCPSP: A technique that pays," European Journal of Operational Research, Elsevier, vol. 165(2), pages 375-386, September.
    11. Kolisch, Rainer & Sprecher, Arno, 1996. "PSPLIB - a project scheduling problem library," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 396, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    12. Bouleimen, K. & Lecocq, H., 2003. "A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version," European Journal of Operational Research, Elsevier, vol. 149(2), pages 268-281, September.
    13. Herroelen, Willy S. & Van Dommelen, Patrick & Demeulemeester, Erik L., 1997. "Project network models with discounted cash flows a guided tour through recent developments," European Journal of Operational Research, Elsevier, vol. 100(1), pages 97-121, July.
    14. Pilar Tormos & Antonio Lova, 2001. "A Competitive Heuristic Solution Technique for Resource-Constrained Project Scheduling," Annals of Operations Research, Springer, vol. 102(1), pages 65-81, February.
    15. Vicente Valls & Francisco Ballestín & Sacramento Quintanilla, 2004. "A Population-Based Approach to the Resource-Constrained Project Scheduling Problem," Annals of Operations Research, Springer, vol. 131(1), pages 305-324, October.
    16. Kolisch, Rainer & Hartmann, Sonke, 2006. "Experimental investigation of heuristics for resource-constrained project scheduling: An update," European Journal of Operational Research, Elsevier, vol. 174(1), pages 23-37, October.
    17. A Sprecher, 2002. "Network decomposition techniques for resource-constrained project scheduling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(4), pages 405-414, April.
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