A new memetic global and local search algorithm for solving hybrid flow shop with multiprocessor task scheduling problem

Engin, Batuhan Eren; Engin, Orhan

doi:10.1007/s42452-020-03895-5

Cited by 10 publications

(2 citation statements)

References 48 publications

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“…As the study by Yeung et al (2004) sets the due window at the center of C max found by Johnson’s rule, where the both ends of time window e and d equal to (0.4 ×C max ) and (0.6× C max ), respectively, we adopted the same approach in our research; however, we used C max values found previously in our study (Engin, 2016) to determine the earliest and latest times of common due window. If a job is completed before the time e , earliness penalty will incur, and if a job is completed after the time d , tardiness penalty will incur, and if a job is completed between the common due window, no penalty will incur.…”

Section: Developed Memetic Algorithmmentioning

confidence: 99%

“…The parameter set used in this study is given in Table IV. This parameter set is formed by Full Factorial Design implemented in the study (Engin, 2016). The penalties per unit time of earliness α j and β j tardiness which are taken 1 for all jobs for the simplicity, since the focus in this study is on developing earliness and tardiness minimization for the first time and to see if the local search approach makes any significant difference.…”

Section: Computational Experimentsmentioning

confidence: 99%

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Hybrid flow shop with multiprocessor task scheduling based on earliness and tardiness penalties

Engin

2018

JEIM

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Purpose Hybrid flow shop with multiprocessor task (HFSMT) has received considerable attention in recent years. The purpose of this paper is to consider an HFSMT scheduling under the environment of a common time window. The window size and location are considered to be given parameters. The research deals with the criterion of total penalty cost minimization incurred by earliness and tardiness of jobs. In this research, a new memetic algorithm in which a global search algorithm is accompanied with the local search mechanism is developed to solve the HFSMT with jobs having a common time window. The operating parameters of memetic algorithm have an important role on the quality of solution. In this paper, a full factorial experimental design is used to determining the best parameters of memetic algorithm for each problem type. Memetic algorithm is tested using HFSMT problems. Design/methodology/approach First, hybrid flow shop scheduling system and hybrid flow shop scheduling with multiprocessor task are defined. The applications of the hybrid flow shop system are explained. Also the background of hybrid flow shop with multiprocessor is given in the introduction. The features of the proposed memetic algorithm are described in Section 2. The experiment results are presented in Section 3. Findings Computational experiments show that the proposed new memetic algorithm is an effective and efficient approach for solving the HFSMT under the environment of a common time window. Originality/value There is only one study about HFSMT scheduling with time window. This is the first study which added the windows to the jobs in HFSMT problems.

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Section: Developed Memetic Algorithmmentioning

confidence: 99%

Section: Computational Experimentsmentioning

confidence: 99%