Bi-objective scheduling for reentrant hybrid flow shop using Pareto genetic algorithm

Cho, Hang-Min; Bae, Seung Yong; Kim, Jungwuk; Jeong, In-Jae

doi:10.1016/j.cie.2011.04.008

Cited by 77 publications

(39 citation statements)

References 24 publications

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“…Three performance metrics [4,11] for the bi-objective optimization are used for comparisons, including the convergence metric (γ), the diversity metric (Δ), and the dominance metric (Ω). The convergence metric measures the convergence of the obtained solutions to the known optimal Pareto front.…”

Section: Performance Metricsmentioning

confidence: 99%

“…The benchmarking instances generated by Cho et al [11] are used for numerical tests. Job number, stage number, machine number, reentrance times, and processing times are random integers from the uniform distributions U [10,20] …”

Section: Computational Experimentsmentioning

confidence: 99%

“…Kim and Lee [10] designed two heuristics to minimize the makespan by considering the total tardiness as a constraint with a certain allowance. To minimize the makespan and the total tardiness simultaneously, Cho et al [11] developed some local-search based Pareto GAs, and Ying et al [4] proposed an iterated Pareto greedy (IPG) algorithm with better performances. To minimize the total workload, Pearn et al [12] proposed three network algorithms to solve an IC final testing scheduling problem with reentry, which is a generalization of the RHFSP.…”

Section: Introductionmentioning

confidence: 99%

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A Pareto-Based Discrete Harmony Search Algorithm for Bi-objective Reentrant Hybrid Flowshop Scheduling Problem

Shen

Wang

Deng

et al. 2015

Advances in Intelligent Systems and Computing

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In this paper, a Pareto-based discrete harmony search (P-DHS) algorithm is proposed to solve the reentrant hybrid flowshop scheduling problem (RHFSP) with the makespan and the total tardiness criteria. For each job, the operation set of each pass is regarded as a sub-job. To adopt the harmony search algorithm to solve the RHFSP, each harmony vector is represented by a discrete sub-job sequence, which determines the priority to allocate all the operations. To handle the discrete representation, a novel improvisation scheme is designed. During the search process, the explored non-dominated solutions are stored in the harmony memory with a dynamic size. The influence of the parameter setting is investigated, and numerical tests are carried out based on some benchmarking instances. The comparisons to some existing algorithms in terms of several performance metrics demonstrate the effectiveness of the P-DHS algorithm.

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Section: Performance Metricsmentioning

confidence: 99%

Section: Computational Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Pareto-Based Discrete Harmony Search Algorithm for Bi-objective Reentrant Hybrid Flowshop Scheduling Problem

Shen

Wang

Deng

et al. 2015

Advances in Intelligent Systems and Computing

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“…They also proposed some heuristic algorithms and a random key genetic algorithm and compare with hybrid genetic algorithm. Cho et al (2011) considered multi-objective re-entrant hybrid flow-shop with identical parallel machines. They suggested local search-based Pareto genetic algorithms to minimize makespan and total tardiness in the shop.…”

Section: Introductionmentioning

confidence: 99%

A variable neighbourhood search for hybrid flow-shop scheduling problem with rework and set-up times

Eskandari

Hosseinzadeh

2014

Journal of the Operational Research Society

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This paper deals with hybrid flow-shop scheduling problem with rework. In this problem, jobs are inspected at the last stage, and poorly processed jobs were returned and processed again. Thus, a job may visit a stage more than once, and we have a hybrid flow-shop with re-entrant flow. This kind of a shop may occur in many industries, such as final inspection system in automotive manufacturing. The criterion is to minimize the makespan of the system. We developed a 0-1 mixed-integer program of the problem. Since the hybrid flow-shop scheduling problem is NP-hard, an algorithm for finding an optimal solution in polynomial time does not exist. So we generalized some heuristic methods based on several basic dispatching rules and proposed a variable neighbourhood search (VNS) for the problem with sequence-dependent set-up times and unrelated parallel machines. The computational experiments show that VNS provides better solutions than heuristic methods.

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“…This problem is solved with a multi-objective GA by using the Lorenz dominance relationship. Cho et al [11] focused on the minimization of makespan and total tardiness in a RHFS. They proposed a local-search algorithm based Pareto GA with Minkowski distance-based crossover operator to achieve good approximate Pareto.…”

Section: Literature Reviewmentioning

confidence: 99%

Bi-objective scheduling for re-entrant hybrid flow shop with learning effect and setup times

et al. 2017

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The production scheduling problem in hybrid flow shops is a complex combinatorial optimization problem observed in many real-world applications. The standard hybrid flow shop problem involves often unrealistic assumptions. In order to address the realistic assumptions, four additional traits were added to the proposed problem. These include re-entrant line, setup times, position-dependent learning effects, and the consideration of maximum completion time together with total tardiness as objective function. Since the proposed problem is non-deterministic polynomial-time (NP)-hard, a meta-heuristic algorithm is proposed as the solution procedure. The solution procedure is categorized as an a priori approach. To show the efficiency and effectiveness of the proposed algorithm, computational experiments were done on various test problems. Computational results show that the proposed algorithm can obtain an effective and appropriate solution quality for our investigated problem.

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Bi-objective scheduling for reentrant hybrid flow shop using Pareto genetic algorithm

Cited by 77 publications

References 24 publications

A Pareto-Based Discrete Harmony Search Algorithm for Bi-objective Reentrant Hybrid Flowshop Scheduling Problem

A Pareto-Based Discrete Harmony Search Algorithm for Bi-objective Reentrant Hybrid Flowshop Scheduling Problem

A variable neighbourhood search for hybrid flow-shop scheduling problem with rework and set-up times

Bi-objective scheduling for re-entrant hybrid flow shop with learning effect and setup times

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