Automatic Algorithm Design for Hybrid Flowshop Scheduling Problems

Alfaro-Fernández, Pedro; Ruíz, Rubén; Pagnozzi, Federico; Stützle, Thomas

doi:10.1016/j.ejor.2019.10.004

Cited by 31 publications

(17 citation statements)

References 42 publications

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“…According to table 3, ADA has an RDI close to the best results for the small benchmark with all CPU times. We also observed that, on average, the proposed HIGT gave better results for small instances with the three stopping times where the average RDI value is 0.73 for the proposed method while the nearest value is given by ADA of Alfaro-Fernández et al (2020) with an average RDI = 1.32. However, our approach shows a reduction of 44.69% against the closest RDI value.…”

Section: Results Evaluation and Statistical Analysesmentioning

confidence: 67%

“…In the literature of HFS, several methods are used with many variants among which we selected 4 from the best methods: the genetic algorithm (GA) of Kahraman et al (2008), the artificial bee colony (ABC) of Pan et al (2012), the improved simulated annealing (HSA) of Naderi et al (2009), the artificial immune system (AIS) of Engin and Döyen (2004). the two methods based on iterated local search ILS V N S and iterated greedy IG V N S of Pan et al (2017a) and finally the auto-designed algorithm (ADA) of Alfaro-Fernández et al (2020). All these seven methods are carefully adapted and re-implemented for the studied problem.…”

Section: Benchmark Competing Methods and Experimental Settingmentioning

confidence: 99%

“…Khare and Agrawal (2019) studied the HFS with sequence depend setup times, in this work, authors proposed three methods based on metaphors: whale optimization algorithm (OBWOA), hybrid squirrel search algorithm (HSSA) and discrete grey wolf optimization (DGWO) to minimize the T W ET . Alfaro-Fernández et al (2020) considered the HFS problem with due window where the objective is the minimization of T W ET . An Auto-designed Algorithm (ADA) based on iterated greedy is used for the resolution.…”

Section: Literature Reviewmentioning

confidence: 99%

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An effective iterated greedy algorithm for blocking hybrid flow shop problem with due date window

Missaoui

Boujelbène

2021

RAIRO-Oper. Res.

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Nowadays many industry consider an interval time as a due date instead of precise points in time. In this study, the hybrid flow shop scheduling problem with basic blocking constraint is tackled. Where jobs, if done within a due window, are deemed on time. Therefore, the criterion is to minimize the sum of weighted earliness and tardiness. This variant of the hybrid flowshop problem is not investigated to the best of our knowledge. we introduced a new metaheuristic centered on the iterated greedy approach. to evaluate the proposed method we start by the re-implementation and the comparison of seven well-selected procedures that treat the hybrid flowshop problem. In order to prove the robustness of our method, we evaluated it using a new benchmark of more than 1000 instances. The experimental results demonstrated that the proposed algorithm is effective and produces a very high solution.

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Section: Results Evaluation and Statistical Analysesmentioning

confidence: 67%

Section: Benchmark Competing Methods and Experimental Settingmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

An effective iterated greedy algorithm for blocking hybrid flow shop problem with due date window

Missaoui

Boujelbène

2021

RAIRO-Oper. Res.

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“…Therefore, the use of meta-heuristic algorithms should be considered. Statistical calculations showed that the designed automatic algorithm is more efficient than other algorithms in solving the problem [26]. Lee et al, modeled a hybrid flow shop scheduling model using sequence-dependent preparation times.…”

Section: Literature Reviewmentioning

confidence: 99%

The Problem of Uninterrupted Hybrid Flow Shop Scheduling with Regard to the Fuzzy Processing Time

Kian

2021

IJIMES

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In this paper, an uninterrupted hybrid flow shop scheduling problem is modeled under uncertainty conditions. Due to the uncertainty of processing time in workshops, which is due to delays in receiving raw materials or machine failure, fuzzy programming method has been used to control the processing time parameter. In the proposed model, there are several jobs that must be processed by machines in sequence. The main purpose of the proposed model is to determine the correct sequence of operations and assign operations to each machine at each stage, so that the total completion time (Cmax) is minimized. Methodology: In this paper, the fuzzy programming method is used to control the uncertain parameter. Also, The GAMS software and CPLEX solver have also been used to solve the sample problems. Findings: The results of solving the problem in small and medium size show that with increasing the rate of uncertainty, the amount of processing time increases and therefore the completion time of the whole work increases. On the other hand, with the increase in the number of machines in each stage due to the high efficiency of the machines, the completion time of all works has decreased. Originality/Value: The most important innovation of this article is the design of uninterrupted hybrid flow shop scheduling with regard to the fuzzy processing time.

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“…The hybridization of different kinds of SLS algorithms has shown to be able to generate state‐of‐the‐art algorithms when applied to permutation flowshop (Marmion et al., 2013; Pagnozzi and Stützle, 2019) as well as hybrid flowshop (Alfaro‐Fernández et al., 2020), the unconstrained binary quadratic programming and the traveling salesman problem with time windows (López‐Ibáñez et al., 2017). However, allowing hybridization can generate huge parameter spaces and generate algorithms with a complex, nested structure.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the impact of grammar complexity in automatic algorithm design

Pagnozzi

Stützle

2020

Int Trans Operational Res

Self Cite

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Grammar-based automatic algorithm design has been shown to generate stochastic local search algorithms that compete with or outperform state-of-the-art methods. In such systems, algorithms are divided in components and a grammar is used to describe how to properly combine the components to create a working algorithm. In our approach, the grammar is converted in parameters and an automatic parameter configuration tool is used to find the best configuration. This approach allows to consider and hybridize different metaheuristic templates producing combinations never tested before, but this flexibility leads to a very large configuration space to explore. Is such complexity really needed to achieve state-of-the-art performance? In this paper, we investigate this question by creating grammars that allow the hybridization of stochastic local search algorithms at most two, one or zero times. We use these grammars to generate algorithms for the three most studied objectives of the permutation flowshop problem: makespan, total completion time and total tardiness. The generated algorithms are compared using benchmark sets from the literature as well as a quantitative measure of algorithm complexity using a metric based on concept directed acyclic graphs. The experiments show that our system tends to generate hybridized algorithms only when they can provide a substantial performance improvement. On the contrary, when such algorithms do not improve performance, the system generates simpler algorithms regardless of the grammar used.

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Automatic Algorithm Design for Hybrid Flowshop Scheduling Problems

Cited by 31 publications

References 42 publications

An effective iterated greedy algorithm for blocking hybrid flow shop problem with due date window

An effective iterated greedy algorithm for blocking hybrid flow shop problem with due date window

The Problem of Uninterrupted Hybrid Flow Shop Scheduling with Regard to the Fuzzy Processing Time

Evaluating the impact of grammar complexity in automatic algorithm design

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