Expert Systems with Applications, Год журнала: 2024, Номер unknown, С. 125573 - 125573
Опубликована: Окт. 1, 2024
Язык: Английский
Expert Systems with Applications, Год журнала: 2024, Номер unknown, С. 125573 - 125573
Опубликована: Окт. 1, 2024
Язык: Английский
Engineering Applications of Artificial Intelligence, Год журнала: 2025, Номер 145, С. 110211 - 110211
Опубликована: Фев. 19, 2025
Язык: Английский
Процитировано
3Waste Management, Год журнала: 2025, Номер 196, С. 93 - 105
Опубликована: Фев. 21, 2025
Язык: Английский
Процитировано
1Advanced Engineering Informatics, Год журнала: 2024, Номер 62, С. 102895 - 102895
Опубликована: Окт. 1, 2024
Язык: Английский
Процитировано
3Computers & Industrial Engineering, Год журнала: 2025, Номер unknown, С. 111210 - 111210
Опубликована: Май 1, 2025
Язык: Английский
Процитировано
0Processes, Год журнала: 2025, Номер 13(6), С. 1675 - 1675
Опубликована: Май 27, 2025
The remanufacturing of end-of-life products is an effective approach to alleviating resource shortages, environmental pollution, and global warming. As the initial step in process, quality efficiency disassembly have a decisive impact on entire workflow. However, complexity product structures poses numerous challenges practical operations. These include not only conventional precedence constraints among tasks but also sequential dependencies, where interference between due their execution order can prolong operation times complicate formulation plans. Additionally, inherent uncertainties process further affect applicability Therefore, developing reliable plans must fully consider both dependencies uncertainties. To this end, paper employs chance-constrained programming model characterise uncertain information constructs multi-objective sequence-dependent line balancing (MO-SDDLB) problem under environments. aims minimise hazard index, workstation time variance, energy consumption, achieving multi-dimensional optimisation process. efficiently solve problem, designs innovative adaptive large neighbourhood search (MO-ALNS) algorithm. algorithm integrates three destruction repair operators, combined with simulated annealing, roulette wheel selection, local strategies, significantly enhancing solution quality. Practical experiments lithium-ion battery validate effectiveness proposed Moreover, MO-ALNS demonstrated superior performance compared other state-of-the-art methods. On average, against best competitor results, improved number Pareto solutions (NPS) by approximately 21%, reduced inverted generational distance (IGD) about increased hypervolume (HV) nearly 8%. Furthermore, exhibited stability, providing feasible for optimisation.
Язык: Английский
Процитировано
0Expert Systems with Applications, Год журнала: 2024, Номер unknown, С. 125573 - 125573
Опубликована: Окт. 1, 2024
Язык: Английский
Процитировано
1