Effective Hybrid Stochastic Local Search Algorithms for Biobjective Permutation Flowshop Scheduling

  • Jérémie Dubois-Lacoste
  • Manuel López-Ibáñez
  • Thomas Stützle
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5818)


This paper presents the steps followed in the design of hybrid stochastic local search algorithms for biobjective permutation flow shop scheduling problems. In particular, this paper tackles the three pairwise combinations of the objectives (i) makespan, (ii) the sum of the completion times of the jobs, and (iii) the weighted total tardiness of all jobs. The proposed algorithms are combinations of two local search methods: two-phase local search and Pareto local search. The design of the algorithms is based on a careful experimental analysis of crucial algorithmic components of the two search methods. The final results show that the newly developed algorithms reach very high performance: The solutions obtained frequently improve upon the best nondominated solutions previously known, while requiring much shorter computation times.


Schedule Problem Local Search Pareto Front Nondominated Solution Biobjective Problem 
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 2009

Authors and Affiliations

  • Jérémie Dubois-Lacoste
    • 1
  • Manuel López-Ibáñez
    • 1
  • Thomas Stützle
    • 1
  1. 1.IRIDIA, CoDEUniversité Libre de BruxellesBrusselsBelgium

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