Flow Shop Scheduling Using a General Approach for Differential Evolution

  • Frederico Gadelha Guimarães
  • Rodrigo César Pedrosa Silva
  • Ricardo Sérgio Prado
  • Oriane Magela Neto
  • Donald David Davendra
Part of the Intelligent Systems Reference Library book series (ISRL, volume 38)


This chapter presents a general framework of Differential Evolution algorithm for combinatorial optimization problems. We define the differences between a given pair of solutions in the differential mutation as a set of elementary movements in the discrete search space. In this way, the search mechanism and self-adaptive behavior of the differential evolution is preserved and generalized to combinatorial problems. These ideas are then applied to n-job m-machine flow shop scheduling in order to illustrate its application in an important problem in combinatorial optimization. The method was applied to the 120 Taillard instances of the permutation flow shop scheduling problem, and compared against the results obtained by other metaheuristic algorithms in the literature. Although relying only on the differential mutation and the local search performed on the best individual, dDE ranks fairly well against more sophisticated metaheuristics. The results are promising and illustrate the applicability of the proposed approach for combinatorial optimization using differential evolution.


Local Search Differential Evolution Differential Evolution Algorithm Trial Vector Elementary Movement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Frederico Gadelha Guimarães
    • 1
  • Rodrigo César Pedrosa Silva
    • 1
  • Ricardo Sérgio Prado
    • 2
  • Oriane Magela Neto
    • 1
  • Donald David Davendra
    • 3
  1. 1.Departamento de Engenharia ElétricaUniversidade Federal de Minas GeraisBelo HorizonteBrazil
  2. 2.Instituto Federal Minas GeraisOuro PretoBrazil
  3. 3.Department of Computer Science, Faculty of Electrical Engineering and Computer ScienceVB-Technical University of OstravaOstravaCzech Republic

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