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Heuristic solution methods for the stochastic flow shop problem

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  • Baker, Kenneth R.
  • Altheimer, Dominik

Abstract

We investigate the stochastic flow shop problem with m machines and general distributions for processing times. No analytic method exists for solving this problem, so we looked instead at heuristic methods. We devised three constructive procedures with modest computational requirements, each based on approaches that have been successful at solving the deterministic counterpart. We compared the performance of these procedures experimentally on a set of test problems and found that all of them achieve near-optimal performance.

Suggested Citation

  • Baker, Kenneth R. & Altheimer, Dominik, 2012. "Heuristic solution methods for the stochastic flow shop problem," European Journal of Operational Research, Elsevier, vol. 216(1), pages 172-177.
    • Handle: RePEc:eee:ejores:v:216:y:2012:i:1:p:172-177
    DOI: 10.1016/j.ejor.2011.07.021
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    References listed on IDEAS

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    Cited by:

    1. Framinan, Jose M. & Perez-Gonzalez, Paz, 2015. "On heuristic solutions for the stochastic flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 246(2), pages 413-420.
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    3. Juan, Angel A. & Faulin, Javier & Grasman, Scott E. & Rabe, Markus & Figueira, Gonçalo, 2015. "A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems," Operations Research Perspectives, Elsevier, vol. 2(C), pages 62-72.
    4. Romero-Silva, Rodrigo & Shaaban, Sabry & Marsillac, Erika & Hurtado, Margarita, 2018. "Exploiting the characteristics of serial queues to reduce the mean and variance of flow time using combined priority rules," International Journal of Production Economics, Elsevier, vol. 196(C), pages 211-225.

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