A novel hybrid meta-heuristic algorithm for a no-wait flexible flow shop scheduling problem with sequence dependent setup times

Jolai, Fariborz; Rabiee, Meysam; Asefi, Hossein

doi:10.1080/00207543.2011.653012

Cited by 68 publications

(23 citation statements)

References 39 publications

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“…Logendran et al (2006) studied two machine group scheduling problems in discrete parts manufacturing with sequence dependent setup times. Jolai et al (2012) presented a novel metaheuristic algorithm for solving no-wait flexible flow shop with sequence dependent setup times. Gholami et al (2009) solved hybrid flow shop with sequence dependent setup times with condition of random machine breakdown.…”

Section: Literature Reviewmentioning

confidence: 99%

Solving group scheduling problem in no-wait flexible flowshop with random machine breakdown

Adressi

Hassanpour²,

Azizi³

2016

10.5267/j.dsl

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Section: Literature Reviewmentioning

confidence: 99%

Solving group scheduling problem in no-wait flexible flowshop with random machine breakdown

Adressi

Hassanpour²,

Azizi³

2016

10.5267/j.dsl

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“…(1) Wait between two consecutive operations of a job: if the no-wait constraint occurs, two successive operations of a job must be processed without any interruption and thus no-wait models are established in different environments: flow shop [55][56][57][58][59][60], hybrid/flexible workshop [61][62][63][64][65], job shop ( [47,[66][67][68]), and open shop [47,54,69].…”

Section: Quantitative Illustrationmentioning

confidence: 99%

A Survey of Recent Research on Optimization Models and Algorithms for Operations Management from the Process View

Fei

Shen

2017

Scientific Programming

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Over the past decades, optimization in operations management has grown ever more popular not only in the academic literature but also in practice. However, the problems have varied a lot, and few literature reviews have provided an overview of the models and algorithms that are applied to the optimization in operations management. In this paper, we first classify crucial optimization areas of operations management from the process point of view and then analyze the current status and trends of the studies in those areas. The purpose of this study is to give an overview of optimization modelling and resolution approaches, which are applied to operations management.

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“…However, for many practical problems, this assumption cannot hold, because the machine setup operation is unavoidable when changing job on the machinery. Specifically as shown in Jolai et al (2012), it would be a waste of about 20% of available machine capability only because the setup times are not handled properly. According to Ulungu et al (1999), the setup times depend on the job that is about to be processed and the one the machine most recently processed is called sequence dependent setup times (in the opposite, the setup times only depend on the job that is about to be processed is called sequence independent setup times).…”

Section: Introductionmentioning

confidence: 99%

Multiple rules with game theoretic analysis for flexible flow shop scheduling problem with component altering times

Han

Zhu

et al. 2016

IJMIC

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This paper studies the flexible flow shop scheduling problem with component altering times (FFSP-CAT), which is a specific form of the flexible flow shop scheduling problem with sequence dependent setup times in the practical scenario. Dealing with FFSP-CAT includes the jobs' machine assignment determination and the globe optimisation. We develop six rules for jobs' machine assignment, and since these rules will easily conflict with one another if they are used with the same priorities, we construct a repeated cooperative model and provide a game theoretical analysis, then derive a Nash equilibrium machine assignment scheme (NEMAS) to effectively manage these rules for jobs' machines assignment at each stage. Furthermore, to achieve the global optimum, we design an advanced compact genetic algorithm (ACGA). By combining NEMAS and ACGA, an approach named advanced compact genetic algorithm with Nash equilibrium machine assignment scheme (ACGA-NEMAS) is used for minimising the makespan of FFSP-CAT. Through extensive comparison experiments with different scales of instances, we show that the algorithm with NEMAS acquires 56.85% improvement over the algorithm without NEMAS, and ACGA-NEMAS performs 80.28% better than genetic algorithm.

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A novel hybrid meta-heuristic algorithm for a no-wait flexible flow shop scheduling problem with sequence dependent setup times

Cited by 68 publications

References 39 publications

Solving group scheduling problem in no-wait flexible flowshop with random machine breakdown

Solving group scheduling problem in no-wait flexible flowshop with random machine breakdown

A Survey of Recent Research on Optimization Models and Algorithms for Operations Management from the Process View

Multiple rules with game theoretic analysis for flexible flow shop scheduling problem with component altering times

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