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Solving the response time variability problem by means of a genetic algorithm

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  • García-Villoria, Alberto
  • Pastor, Rafael

Abstract

The response time variability problem (RTVP) is a hard scheduling problem that has recently been defined in the literature and has a wide range of real-world applications in mixed-model assembly lines, multithreaded computer systems, network environments and others. The RTVP arises whenever products, clients or jobs need to be sequenced in such a way that the variability in the time between the points at which they receive the necessary resources is minimized. Since the RTVP is a complex problem, heuristic and metaheuristic techniques are needed to solve it. The best results in the literature for the RTVP have been obtained with a psychoclonal algorithm. We propose a genetic algorithm (GA) that is adapted to solve the RTVP. A computational experiment is carried out and it is shown that, on average, the GA produces better results than the psychoclonal algorithm.

Suggested Citation

  • García-Villoria, Alberto & Pastor, Rafael, 2010. "Solving the response time variability problem by means of a genetic algorithm," European Journal of Operational Research, Elsevier, vol. 202(2), pages 320-327, April.
  • Handle: RePEc:eee:ejores:v:202:y:2010:i:2:p:320-327
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    1. M J Brusco, 2008. "Scheduling advertising slots for television," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(10), pages 1363-1372, October.
    2. Carter, Arthur E. & Ragsdale, Cliff T., 2006. "A new approach to solving the multiple traveling salesperson problem using genetic algorithms," European Journal of Operational Research, Elsevier, vol. 175(1), pages 246-257, November.
    3. John Miltenburg, 1989. "Level Schedules for Mixed-Model Assembly Lines in Just-In-Time Production Systems," Management Science, INFORMS, vol. 35(2), pages 192-207, February.
    4. Belarmino Adenso-Díaz & Manuel Laguna, 2006. "Fine-Tuning of Algorithms Using Fractional Experimental Designs and Local Search," Operations Research, INFORMS, vol. 54(1), pages 99-114, February.
    5. Wu, Xiaodan & Chu, Chao-Hsien & Wang, Yunfeng & Yan, Weili, 2007. "A genetic algorithm for cellular manufacturing design and layout," European Journal of Operational Research, Elsevier, vol. 181(1), pages 156-167, August.
    6. M. L. BALINSKI & H. P. Young, 1982. "Fair Representation in the European Parliament," Journal of Common Market Studies, Wiley Blackwell, vol. 20(4), pages 361-373, June.
    7. Srinivas Bollapragada & Michael R. Bussieck & Suman Mallik, 2004. "Scheduling Commercial Videotapes in Broadcast Television," Operations Research, INFORMS, vol. 52(5), pages 679-689, October.
    8. Kubiak, Wieslaw, 1993. "Minimizing variation of production rates in just-in-time systems: A survey," European Journal of Operational Research, Elsevier, vol. 66(3), pages 259-271, May.
    9. James C. Bean, 1994. "Genetic Algorithms and Random Keys for Sequencing and Optimization," INFORMS Journal on Computing, INFORMS, vol. 6(2), pages 154-160, May.
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    Cited by:

    1. Albert Corominas & Alberto García-Villoria & Rafael Pastor, 2013. "Metaheuristic algorithms hybridised with variable neighbourhood search for solving the response time variability problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 296-312, July.
    2. Chenxia Jin & Fachao Li & Marzana Wilamowska‐Korsak & Ling Li & Liuliu Fu, 2014. "BSP‐GA: A new Genetic Algorithm for System Optimization and Excellent Schema Selection," Systems Research and Behavioral Science, Wiley Blackwell, vol. 31(3), pages 337-352, May.
    3. S. Acharyya & A. K. Datta, 2020. "Matching formulation of the Staff Transfer Problem: meta-heuristic approaches," OPSEARCH, Springer;Operational Research Society of India, vol. 57(3), pages 629-668, September.
    4. García-Villoria, Alberto & Salhi, Said & Corominas, Albert & Pastor, Rafael, 2011. "Hyper-heuristic approaches for the response time variability problem," European Journal of Operational Research, Elsevier, vol. 211(1), pages 160-169, May.

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