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Using iterated local search for solving the flow-shop problem: Parallelization, parametrization, and randomization issues

Author
Juan, Á.; Lourenço, H.; Mateo, M.; Luo, R.; Castella, Q.
Type of activity
Journal article
Journal
International transactions in operational research
Date of publication
2014-01
Volume
21
Number
1
First page
103
Last page
126
DOI
https://doi.org/10.1111/itor.12028 Open in new window
Repository
http://hdl.handle.net/2117/21449 Open in new window
URL
http://onlinelibrary.wiley.com/doi/10.1111/itor.12028/pdf Open in new window
Abstract
Iterated local search (ILS) is a powerful framework for developing efficient algorithms for the permutation flow-shop problem (PFSP). These algorithms are relatively simple to implement and use very few parameters, which facilitates the associated fine-tuning process. Therefore, they constitute an attractive solution for real- life applications. In this paper, we discuss some parallelization, parametrization, and randomization issues related to ILS-based algorithms for solving the PFSP. In parti...
Citation
Juan-Pérez, A. [et al.]. Using iterated local search for solving the flow-shop problem: Parallelization, parametrization, and randomization issues. "International transactions in operational research", Gener 2014, vol. 21, núm. 1, p. 103-126.
Keywords
Biased randomized heuristics, Flow-shop problem, Iterated local search, Metaheuristics, Parallelizable algorithms, Parameters setting, Scheduling
Group of research
SCOM - Supply Chain and Operations Management

Participants

  • Juan Pérez, Ángel Alejandro  (author)
  • Lourenço, Helena R.  (author)
  • Mateo Doll, Manuel  (author)
  • Luo, Rachel  (author)
  • Castellà, Quim  (author)