Two sided disassembly line balancing problem with rest time of works: A constraint programming model and an improved NSGA II algorithm

Xu, ZhenYu; Han, Yong

doi:10.1016/j.eswa.2023.122323

Cited by 5 publications

(1 citation statement)

References 44 publications

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“…2 ⃝ Complete disassembly of all components of the product is required [24]. 3 ⃝ Each disassembly task is limited to a single execution [25]. 4 ⃝ Specialized personnel are allocated to certain workstations and are not permitted to switch workstations [26].…”

Section: Disassembly Line Type Workermentioning

confidence: 99%

Multi-Objective Advantage Actor-Critic Algorithm for Hybrid Disassembly Line Balancing with Multi-Skilled Workers

Wang,

Xi,

Guo

et al. 2024

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The scheduling of disassembly lines is of great importance to achieve optimized productivity. In this paper, we address the Hybrid Disassembly Line Balancing Problem that combines linear disassembly lines and U-shaped disassembly lines, considering multi-skilled workers, and targeting profit and carbon emissions. In contrast to common approaches in reinforcement learning that typically employ weighting strategies to solve multi-objective problems, our approach innovatively incorporates non-dominated ranking directly into the reward function. The exploration of Pareto frontier solutions or better solutions is moderated by comparing performance between solutions and dynamically adjusting rewards based on the occurrence of repeated solutions. The experimental results show that the multi-objective Advantage Actor-Critic algorithm based on Pareto optimization exhibits superior performance in terms of metrics superiority in the comparison of six experimental cases of different scales, with an excellent metrics comparison rate of 70%. In some of the experimental cases in this paper, the solutions produced by the multi-objective Advantage Actor-Critic algorithm show some advantages over other popular algorithms such as the Deep Deterministic Policy Gradient Algorithm, the Soft Actor-Critic Algorithm, and the Non-Dominated Sorting Genetic Algorithm II. This further corroborates the effectiveness of our proposed solution.

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Section: Disassembly Line Type Workermentioning

confidence: 99%