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

Shen, Jing; Wang, Sheng; Deng, Jin; Zheng, Xiaolong

doi:10.1007/978-3-662-47926-1_41

Cited by 8 publications

(3 citation statements)

References 26 publications

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“…The RHFSP addressed in this study can be described as follows [17,26,27]: n jobs need to be processed in s stages in sequence. There are identical parallel machines in the stage i, and each job can be processed on any machine in the corresponding stage.…”

Section: Problem Descriptionmentioning

confidence: 99%

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Multi‐Objective Reentrant Hybrid Flowshop Scheduling with Machines Turning on and off Control Strategy Using Improved Multi‐Verse Optimizer Algorithm

Geng

Cao

et al. 2019

Mathematical Problems in Engineering

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This paper focuses on the multi-objective optimization of the reentrant hybrid flowshop scheduling problem (RHFSP) with machines turning on and off control strategy. RHFSP exhibits significance in many industrial applications, but scheduling with both energy consumption consideration and reentrant concept is relatively unexplored at present. In this study, an improved Multi-Objective Multi-Verse Optimizer (IMOMVO) algorithm is proposed to optimize the RHFSP with objectives of makespan, maximum tardiness, and idle energy consumption. To solve the proposed model more effectively, a series of improved operations are carried out, including population initialization based on Latin hypercube sampling (LHS), individual position updating based on Lévy flight, and chaotic local search based on logical self-mapping. In addition, a right-shift procedure is used to adjust the start time of operations aiming to minimize the idle energy consumption without changing the makespan. Then, Taguchi method is utilized to study the influence of different parameter settings on the scheduling results of the IMOMVO algorithm. Finally, the performance of the proposed IMOMVO algorithm is evaluated by comparing it with MOMVO, MOPSO, MOALO, and NSGA-II on the same benchmark set. The results show that IMOMVO algorithm can solve the RHFSP with machines turning on and off control strategy effectively, and in terms of convergence and diversity of non-dominated solutions, IMOMVO is obviously superior to other algorithms. However, the distribution level of the five algorithms has little difference. Meanwhile, by turning on and off the machine properly, the useless energy consumption in the production process can be reduced effectively.

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Section: Problem Descriptionmentioning

confidence: 99%

“…Ying and Lin et al [15] proposed an efficient iterative Pareto greedy (IPG) algorithm based on the research in [13]. Shen and Wang et al [16,17] proposed an improved teaching and learning optimization algorithm and a Pareto discrete harmony search algorithm to solve the biobjective RHFSP.…”

Section: Introductionmentioning

confidence: 99%

Multi‐Objective Reentrant Hybrid Flowshop Scheduling with Machines Turning on and off Control Strategy Using Improved Multi‐Verse Optimizer Algorithm

Geng

Cao

et al. 2019

Mathematical Problems in Engineering

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show abstract

“…Ying et al [10] used an iterative Pareto greedy algorithm for the bi-objective RHFSP based on the research in [9]. Shen et al [11,12] applied an improved teaching and learning optimization algorithm and a Pareto-based discrete harmony search algorithm to solve the bi-objective RHFSP. Cheng and Lei [13] studied an improved imperialist competition algorithm for the RSP in order to minimise the makespan and total tardiness.…”

Section: Introductionmentioning

confidence: 99%

Bi-Objective Re-Entrant Hybrid Flow Shop Scheduling considering Energy Consumption Cost under Time-of-Use Electricity Tariffs

Geng

Dai

et al. 2020

Complexity

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Re-entrant hybrid flow shop scheduling problem (RHFSP) is widely used in industries. However, little attention is paid to energy consumption cost with the raise of green manufacturing concept. is paper proposes an improved multiobjective ant lion optimization (IMOALO) algorithm to solve the RHFSP with the objectives of minimizing the makespan and energy consumption cost under Time-of-Use (TOU) electricity tariffs. A right-shift operation is then used to adjust the starting time of operations by avoiding the period of high electricity price to reduce the energy consumption cost as far as possible. e experimental results show that IMOALO algorithm is superior to multiobjective ant lion optimization (MOALO) algorithm, NSGA-II, and MOPSO in terms of the convergence, dominance, and diversity of nondominated solutions. e proposed model can make enterprises avoid high price period reasonably, transfer power load, and reduce the energy consumption cost effectively. Meanwhile, parameter analysis indicates that the period of TOU electricity tariffs and energy efficiency of machines have great impact on the scheduling results.

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Considering stockers in reentrant hybrid flow shop scheduling with limited buffer capacity

Lin

Liu

Chen

2020

Computers & Industrial Engineering

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

Cited by 8 publications

References 26 publications

Multi‐Objective Reentrant Hybrid Flowshop Scheduling with Machines Turning on and off Control Strategy Using Improved Multi‐Verse Optimizer Algorithm

Multi‐Objective Reentrant Hybrid Flowshop Scheduling with Machines Turning on and off Control Strategy Using Improved Multi‐Verse Optimizer Algorithm

Bi-Objective Re-Entrant Hybrid Flow Shop Scheduling considering Energy Consumption Cost under Time-of-Use Electricity Tariffs

Considering stockers in reentrant hybrid flow shop scheduling with limited buffer capacity

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