Modeling and Multiobjective Optimization for Energy-Aware Hybrid Flow Shop Scheduling

Ji-hong Yan (), Fen-yang Zhang, Xin Li, Zi-mo Wang and Wei Wang
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Ji-hong Yan: Harbin Institute of Technology
Fen-yang Zhang: Harbin Institute of Technology
Xin Li: Harbin Institute of Technology
Zi-mo Wang: Harbin Institute of Technology
Wei Wang: Harbin Institute of Technology

A chapter in Proceedings of 2013 4th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2013), 2014, pp 741-751 from Springer

Abstract: Abstract In this paper, a multiobjective scheduling problem for energy-aware Hybrid Flow Shop (HFS) is studied, in which minimal makespan and energy consumption are set as the objectives. The energy consumption model of HFS is established, in which the energy consumption is categorized into five parts as Processing Energy (PE), Adjusting Energy (AE), Transport Energy (TE), Waiting Energy (WE) and Routine Energy (RE). Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm (NSGA-2) are applied to obtain optimal schedules. Simulation results demonstrate that the proposed method is effective in supporting energy efficiency management in HSF.

Keywords: Energy consumption model; GA; Hybrid flow shop; NSGA-2 (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-40060-5_71

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DOI: 10.1007/978-3-642-40060-5_71

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