An iterated greedy algorithm with optimization of partial solutions for the makespan permutation flowshop problem

Dubois-Lacoste, Jérémie; Pagnozzi, Federico; Stützle, Thomas

doi:10.1016/j.cor.2016.12.021

Cited by 85 publications

(36 citation statements)

References 19 publications

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“…Insertion-based Local search + Greedy insertion (IA ILS _ GI ). This procedure adapts the procedure of destruction and construction proposed by Dubois-Lacoste et al (2017) . The method performs an insertion-based local search on the partial sequence d , i.e.…”

Section: Iterated-greedy-based Algorithms Iamentioning

confidence: 99%

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Iterated-greedy-based algorithms with beam search initialization for the permutation flowshop to minimise total tardiness

Fernández-Viagas

Valente

Framiñán

2018

Expert Systems with Applications

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The permutation flow shop scheduling problem is one of the most studied operations research related problems. Literally, hundreds of exact and approximate algorithms have been proposed to optimise several objective functions. In this paper we address the total tardiness criterion, which is aimed towards the satisfaction of customers in a make-to-order scenario. Although several approximate algorithms have been proposed for this problem in the literature, recent contributions for related problems suggest that there is room for improving the current available algorithms. Thus, our contribution is twofold: First, we propose a fast beam-search-based constructive heuristic that estimates the quality of partial sequences without a complete evaluation of their objective function. Second, using this constructive heuristic as initial solution, eight variations of an iterated-greedy-based algorithm are proposed. A comprehensive computational evaluation is performed to establish the efficiency of our proposals against the existing heuristics and metaheuristics for the problem.

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Section: Iterated-greedy-based Algorithms Iamentioning

confidence: 99%

“…Fernandez-Viagas and Framinan, 2015b andDubois-Lacoste, Pagnozzi, &Stützle, 2017 ). 1 Despite the preeminence of these two algorithms, recent advances in related scheduling problems have shown that they can be improved: On the one hand, some studies (see e.g.…”

Section: Introductionmentioning

confidence: 99%

Iterated-greedy-based algorithms with beam search initialization for the permutation flowshop to minimise total tardiness

Fernández-Viagas

Valente

Framiñán

2018

Expert Systems with Applications

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“…igper(rd) implements the destruction and construction processes of iterated greedy algorithms, where rd is the number of jobs removed from the current solution (Ruiz and Stützle, 2007). igls(rd, iterative_imp) is analogous to igper(rd) but in addition applies a local search on the partial solution obtained after jobs removal, following the ideas presented by (Dubois-Lacoste et al, 2017). igio(rd) and nrzper(rd) are destruction-construction perturbations that reorder the jobs before construction according to a non-increasing sum of processing times or the RZ heuristic respectively.…”

Section: Emili Componentsmentioning

confidence: 99%

Automatic Algorithm Design for Hybrid Flowshop Scheduling Problems

Alfaro-Fernández

Ruíz

Pagnozzi

et al. 2020

European Journal of Operational Research

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Industrial production scheduling problems are challenges that researchers have been trying to solve for decades. Many practical scheduling problems such as the hybrid flowshop are N P-hard. As a result, researchers resort to metaheuristics to obtain e ective and e cient solutions. The traditional design process of metaheuristics is mainly manual, often metaphor-based, biased by previous experience and prone to producing overly tailored methods that only work well on the tested problems and objectives. In this paper, we use an Automatic Algorithm Design (AAD) methodology to eliminate these limitations. AAD is capable of composing algorithms from components with minimal human intervention. We test the proposed AAD for three di erent optimization objectives in the hybrid flowshop. Comprehensive computational and statistical testing demonstrates that automatically designed algorithms outperform specifically tailored state-of-the-art methods for the tested objectives in most cases.

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“…The great advantages of this method are as follows: it is simple to implement and has been confirmed to yield high-quality solutions for flow shop problems [52]. The IG has been extensively employed for the last ten years in the scheduling research, especially in the (permutation or hybrid) flow shop problem, for example, Pan and Ruiz [53], Msakni et al [54], Dubois-Lacoste et al [55], and Pan et al [56]. In this study, we propose an IG algorithm with four different local search methods, i.e., four versions of IG, coded as IGLS1, IGLS2, IGLS3, and IGLS4.…”

Section: Iterated Greedy Algorithmmentioning

confidence: 99%

Minimizing the Makespan for a Two-Stage Three-Machine Assembly Flow Shop Problem with the Sum-of-Processing-Time Based Learning Effect

Lin

2018

Discrete Dynamics in Nature and Society

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Two-stage production process and its applications appear in many production environments. Job processing times are usually assumed to be constant throughout the process. In fact, the learning effect accrued from repetitive work experiences, which leads to the reduction of actual job processing times, indeed exists in many production environments. However, the issue of learning effect is rarely addressed in solving a two-stage assembly scheduling problem. Motivated by this observation, the author studies a two-stage three-machine assembly flow shop problem with a learning effect based on sum of the processing times of already processed jobs to minimize the makespan criterion. Because this problem is proved to be NP-hard, a branch-and-bound method embedded with some developed dominance propositions and a lower bound is employed to search for optimal solutions. A cloud theory-based simulated annealing (CSA) algorithm and an iterated greedy (IG) algorithm with four different local search methods are used to find near-optimal solutions for small and large number of jobs. The performances of adopted algorithms are subsequently compared through computational experiments and nonparametric statistical analyses, including the Kruskal–Wallis test and a multiple comparison procedure.

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An iterated greedy algorithm with optimization of partial solutions for the makespan permutation flowshop problem

Cited by 85 publications

References 19 publications

Iterated-greedy-based algorithms with beam search initialization for the permutation flowshop to minimise total tardiness

Iterated-greedy-based algorithms with beam search initialization for the permutation flowshop to minimise total tardiness

Automatic Algorithm Design for Hybrid Flowshop Scheduling Problems

Minimizing the Makespan for a Two-Stage Three-Machine Assembly Flow Shop Problem with the Sum-of-Processing-Time Based Learning Effect

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