A computational study of the permutation flow shop problem based on a tight lower bound

Ladhari, Talel; Haouari, Mohamed

doi:10.1016/j.cor.2003.12.001

Cited by 46 publications

(26 citation statements)

References 35 publications

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“…To test how difficult it is to solve an instance we have on the one hand, two effective algorithms for the permutation flowshop scheduling problem with the objective to minimise the makespan (Ruiz et al, 2006 andStützle, 2007). On the other hand, four lower bounds, one from Taillard (1993) and the three best polynomial bounds of Ladhari and Haouari (2005), proposed for the same problem, are computed for each instance. All the generated instances (48,000 small and 24,000 large) are solved by the two effective algorithms, denoted as HGA (Ruiz et al, 2006) and IG (Ruiz and Stützle, 2007), since they are considered the most effective for this problem.…”

Section: Generationmentioning

confidence: 99%

New hard benchmark for flowshop scheduling problems minimising makespan

Vallada

Ruíz

Framiñán

2015

European Journal of Operational Research

155

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In this work a new benchmark of hard instances for the permutation flowshop scheduling problem with the objective of minimising the makespan is proposed. The new benchmark consists of 240 large instances and 240 small instances with up to 800 jobs and 60 machines. One of the objectives of the work is to generate a benchmark which satisfies the desired characteristics of any benchmark: comprehensive, amenable for statistical analysis and discriminant when several algorithms are compared. An exhaustive experimental procedure is carried out in order to select the hard instances, generating thousands of instances and selecting the hardest ones from the point of view of a gap computed as the difference between very good upper and lower bounds for each instance. Extensive generation and computational experiments, which have taken almost six years of combined CPU time, demonstrate that the proposed benchmark is harder and with more discriminant power than the most common benchmark from the literature. Moreover, a website is developed for researchers in order to share sets of instances, best known solutions and lower bounds, etc. for any combinatorial optimisation problem.

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Section: Generationmentioning

confidence: 99%

New hard benchmark for flowshop scheduling problems minimising makespan

Vallada

Ruíz

Framiñán

2015

European Journal of Operational Research

155

View full text Add to dashboard Cite

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“…Taillard (1993) introduced a data structure that reduces the NEH complexity and speeds up the computation. The NEH heuristic is the most used heuristic to obtain initial solutions for the PFSP within metaheuristics and exact algorithms (Companys & Mateo, 2007;Ladhari & Haouari, 2005).…”

Section: Hybridizing An Ils Metaheuristics With Biased Randomization mentioning

confidence: 99%

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

Ferrer

Guimarans

Ramalhinho

et al. 2016

Expert Systems with Applications

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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.

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“…In this implementation, a fast, simple, lower bound for the makespan that could be computed in O(nm) was selected. This lower bound is denoted as LB1 in the review by Ladhari and Haouari (2005). More specifically, LB1 is a one-machine relaxation of the problem under consideration, in which all j jobs are set a release date r lj = l−1 i=1 p ij (or r j = 0 if l = 1) and a delivery time q lj = m i=l+1 p ij (or q j = 0 if l = m).…”

Section: Implementation: the Permutation Flowshop Scheduling Problem mentioning

confidence: 99%

“…This problem is a well-known combinatorial optimization problem, and we refer the reader to Grabowski and Wodecki (2004) and Ladhari and Haouari (2005) for the latest developments concerning this problem. In our implementation of the proposed algorithm, the following decisions were adopted:…”

Section: Implementation: the Permutation Flowshop Scheduling Problem mentioning

confidence: 99%

A proposal for a hybrid meta-strategy for combinatorial optimization problems

Framiñán

Pastor

2007

J Heuristics

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In this paper, we propose an algorithm named BDS (Bound-Driven Search) that combines features of exact and approximate methods. The proposed procedure may be seen as a local search algorithm that systematically explores (in a branchand bound sense) the most promising nodes, thus preventing solutions from being reevaluated. Additionally, it can be regarded as an exact method as it may be able to guarantee that the solution found is optimal. We present the application of this new algorithm to a specific problem domain: the permutation flow shop scheduling problem with makespan objective. The subsequent computational experiments are encouraging, as the algorithm is able to yield exact or near exact solutions to most instances of the problem. Furthermore, the algorithm outperforms one of the best state-of-the-art algorithms for the problem.

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A computational study of the permutation flow shop problem based on a tight lower bound

Cited by 46 publications

References 35 publications

New hard benchmark for flowshop scheduling problems minimising makespan

New hard benchmark for flowshop scheduling problems minimising makespan

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

A proposal for a hybrid meta-strategy for combinatorial optimization problems

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