A BRILS metaheuristic for non-smooth flow-shop problems with failure-risk costs

Ferrer, Alberto; Guimarans, Daniel; Ramalhinho-Lourenço, Helena; Juan, Angel A.

doi:http://dx.doi.org/10.1016/j.eswa.2015.09.011

A BRILS metaheuristic for non-smooth flow-shop problems with failure-risk costs

Citació

Ferrer A, Guimarans D, Ramalhinho HR, Juan AA. A BRILS metaheuristic for non-smooth flow-shop problems with failure-risk costs. Expert Syst Appl. 2016 Feb;44:177–86. DOI: 10.1016/j.eswa.2015.09.011

Resum

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.