Multi-objective optimization for energy-efficient hybrid flow shop scheduling problem in panel furniture intelligent manufacturing with transportation constraints

The manufacture of customized panel furniture today faces significant environmental challenges in terms of energy consumption and the associated impact on the environment. From an operations management perspective, the energy efficiency of production systems is greatly influenced by production sched...

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Veröffentlicht in:Expert systems with applications Jg. 274; S. 126830
Hauptverfasser: Yue, Xinyi, Xiong, Xianqing, Zhang, Mei, Xu, Xiutong, Yang, Lujie
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 15.05.2025
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Abstract The manufacture of customized panel furniture today faces significant environmental challenges in terms of energy consumption and the associated impact on the environment. From an operations management perspective, the energy efficiency of production systems is greatly influenced by production scheduling. Therefore, to solve the problem of energy-efficient hybrid flow shop scheduling problem (HFSP) for panel furniture manufacturing, we construct a standard mathematical model to trade-off between makespan and total energy consumption. A hybrid VNS-NSGA-II algorithm is proposed, which combines the variable neighborhood search (VNS) and the non-dominated sorting genetic algorithm II (NSGA-II) based on double chain coding and the greedy insertion method decoding rule, aiming to provide a set of compromise solutions. To evaluate the effectiveness of this algorithm, the performance results are analyzed with other five multi-objective optimization algorithms (MOEA/D, SPEA2, MOPSO, MOSA and AdaW). The VNS-NSGA-II algorithm provides promising results for HFSP in panel furniture manufacturing. In addition, the results of the optimal scheduling scheme obtained through the decision-making method are used to evaluate the performance of the proposed model and algorithm in a real-world panel furniture manufacturing scenario. This may provide valuable insights for furniture companies in developing energy-efficient scheduling management.
AbstractList The manufacture of customized panel furniture today faces significant environmental challenges in terms of energy consumption and the associated impact on the environment. From an operations management perspective, the energy efficiency of production systems is greatly influenced by production scheduling. Therefore, to solve the problem of energy-efficient hybrid flow shop scheduling problem (HFSP) for panel furniture manufacturing, we construct a standard mathematical model to trade-off between makespan and total energy consumption. A hybrid VNS-NSGA-II algorithm is proposed, which combines the variable neighborhood search (VNS) and the non-dominated sorting genetic algorithm II (NSGA-II) based on double chain coding and the greedy insertion method decoding rule, aiming to provide a set of compromise solutions. To evaluate the effectiveness of this algorithm, the performance results are analyzed with other five multi-objective optimization algorithms (MOEA/D, SPEA2, MOPSO, MOSA and AdaW). The VNS-NSGA-II algorithm provides promising results for HFSP in panel furniture manufacturing. In addition, the results of the optimal scheduling scheme obtained through the decision-making method are used to evaluate the performance of the proposed model and algorithm in a real-world panel furniture manufacturing scenario. This may provide valuable insights for furniture companies in developing energy-efficient scheduling management.
ArticleNumber 126830
Author Xu, Xiutong
Yang, Lujie
Xiong, Xianqing
Yue, Xinyi
Zhang, Mei
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  givenname: Xianqing
  orcidid: 0000-0002-1877-2805
  surname: Xiong
  fullname: Xiong, Xianqing
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  organization: College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, PR China
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  givenname: Mei
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  organization: College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, PR China
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  givenname: Xiutong
  orcidid: 0000-0002-7069-7523
  surname: Xu
  fullname: Xu, Xiutong
  organization: College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, PR China
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  givenname: Lujie
  surname: Yang
  fullname: Yang, Lujie
  organization: College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, PR China
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Keywords Multi-objective optimization
Hybrid flow shop scheduling problem
Variable neighborhood search
Customized panel furniture
Non-dominated solution genetic algorithm
Energy-efficient scheduling
Language English
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Snippet The manufacture of customized panel furniture today faces significant environmental challenges in terms of energy consumption and the associated impact on the...
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SubjectTerms Customized panel furniture
Energy-efficient scheduling
Hybrid flow shop scheduling problem
Multi-objective optimization
Non-dominated solution genetic algorithm
Variable neighborhood search
Title Multi-objective optimization for energy-efficient hybrid flow shop scheduling problem in panel furniture intelligent manufacturing with transportation constraints
URI https://dx.doi.org/10.1016/j.eswa.2025.126830
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