A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing

Remanufacturing prolongs the life cycle and increases the residual value of various end-of-life (EoL) products. As an inevitable process in remanufacturing, disassembly plays an essential role in retrieving the high-value and useable components of EoL products. To disassemble massive quantities and...

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Main Authors: Youxi Hu, Chao Liu, Ming Zhang, Yu Jia, Yuchun Xu
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/23/3/1652
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author Youxi Hu
Chao Liu
Ming Zhang
Yu Jia
Yuchun Xu
author_facet Youxi Hu
Chao Liu
Ming Zhang
Yu Jia
Yuchun Xu
author_sort Youxi Hu
collection DOAJ
description Remanufacturing prolongs the life cycle and increases the residual value of various end-of-life (EoL) products. As an inevitable process in remanufacturing, disassembly plays an essential role in retrieving the high-value and useable components of EoL products. To disassemble massive quantities and multi-types of EoL products, disassembly lines are introduced to improve the cost-effectiveness and efficiency of the disassembly processes. In this context, disassembly line balancing problem (DLBP) becomes a critical challenge that determines the overall performance of disassembly lines. Currently, the DLBP is mostly studied in straight disassembly lines using single-objective optimization methods, which cannot represent the actual disassembly environment. Therefore, in this paper, we extend the mathematical model of the basic DLBP to stochastic parallel complete disassembly line balancing problem (DLBP-SP). A novel simulated annealing-based hyper-heuristic algorithm (HH) is proposed for multi-objective optimization of the DLBP-SP, considering the number of workstations, working load index, and profits. The feasibility, superiority, stability, and robustness of the proposed HH algorithm are validated through computational experiments, including a set of comparison experiments and a case study of gearboxes disassembly. To the best of our knowledge, this research is the first to introduce gearboxes as a case study in DLBP which enriches the research on disassembly of industrial equipment.
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spelling doaj.art-77896dd4626b4a2e95dd1bdbec769f492023-11-16T18:04:10ZengMDPI AGSensors1424-82202023-02-01233165210.3390/s23031652A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart RemanufacturingYouxi Hu0Chao Liu1Ming Zhang2Yu Jia3Yuchun Xu4College of Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UKCollege of Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UKCollege of Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UKCollege of Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UKCollege of Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UKRemanufacturing prolongs the life cycle and increases the residual value of various end-of-life (EoL) products. As an inevitable process in remanufacturing, disassembly plays an essential role in retrieving the high-value and useable components of EoL products. To disassemble massive quantities and multi-types of EoL products, disassembly lines are introduced to improve the cost-effectiveness and efficiency of the disassembly processes. In this context, disassembly line balancing problem (DLBP) becomes a critical challenge that determines the overall performance of disassembly lines. Currently, the DLBP is mostly studied in straight disassembly lines using single-objective optimization methods, which cannot represent the actual disassembly environment. Therefore, in this paper, we extend the mathematical model of the basic DLBP to stochastic parallel complete disassembly line balancing problem (DLBP-SP). A novel simulated annealing-based hyper-heuristic algorithm (HH) is proposed for multi-objective optimization of the DLBP-SP, considering the number of workstations, working load index, and profits. The feasibility, superiority, stability, and robustness of the proposed HH algorithm are validated through computational experiments, including a set of comparison experiments and a case study of gearboxes disassembly. To the best of our knowledge, this research is the first to introduce gearboxes as a case study in DLBP which enriches the research on disassembly of industrial equipment.https://www.mdpi.com/1424-8220/23/3/1652disassembly line balancing problemhyper-heuristic algorithmmulti-objective optimisationdisassemblyremanufacturing
spellingShingle Youxi Hu
Chao Liu
Ming Zhang
Yu Jia
Yuchun Xu
A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing
Sensors
disassembly line balancing problem
hyper-heuristic algorithm
multi-objective optimisation
disassembly
remanufacturing
title A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing
title_full A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing
title_fullStr A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing
title_full_unstemmed A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing
title_short A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing
title_sort novel simulated annealing based hyper heuristic algorithm for stochastic parallel disassembly line balancing in smart remanufacturing
topic disassembly line balancing problem
hyper-heuristic algorithm
multi-objective optimisation
disassembly
remanufacturing
url https://www.mdpi.com/1424-8220/23/3/1652
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