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http://hdl.handle.net/10609/92914
Title: | A BRILS metaheuristic for non-smooth flow-shop problems with failure-risk costs |
Author: | Ferrer, Albert Guimarans, Daniel Ramalhinho Lourenco, Helena Juan, Angel A. |
Others: | Universitat Politècnica de Catalunya (UPC) National ICT Australia Universitat Pompeu Fabra Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3) |
Citation: | Ferrer Biosca, A., Guimarans, D., Ramalhinho, H. & Juan, A.A. (2016). A BRILS metaheuristic for non-smooth flow-shop problems with failure-risk costs. Expert Systems with Applications, 44(), 177-186. doi: 10.1016/j.eswa.2015.09.011 |
Abstract: | This paper analyzes a realistic variant of the Permutation Flow-Shop Problem (PFSP) by considering a non-smooth objective function that takes into account not only the traditional makespan cost but also failure-risk costs due to uninterrupted operation of machines. After completing a literature review on the issue, the paper formulates an original mathematical model to describe this new PFSP variant. Then, a Biased-Randomized Iterated Local Search (BRILS) algorithm is proposed as an efficient solving approach. An oriented (biased) random behavior is introduced in the well-known NEH heuristic to generate an initial solution. From this initial solution, the algorithm is able to generate a large number of alternative good solutions without requiring a complex setting of parameters. The relative simplicity of our approach is particularly useful in the presence of non-smooth objective functions, for which exact optimization methods may fail to reach their full potential. The gains of considering failure-risk costs during the exploration of the solution space are analyzed throughout a series of computational experiments. To promote reproducibility, these experiments are based on a set of traditional benchmark instances. Moreover, the performance of the proposed algorithm is compared against other state-of-the-art metaheuristic approaches, which have been conveniently adapted to consider failure-risk costs during the solving process. The proposed BRILS approach can be easily extended to other combinatorial optimization problems with similar non-smooth objective functions. |
Keywords: | biased randomization heuristic algorithms flow shop scheduling iterated local search |
DOI: | 10.1016/j.eswa.2015.09.011 |
Document type: | info:eu-repo/semantics/article |
Issue Date: | 1-Feb-2016 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Articles cientÍfics Articles |
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