RETRACTED ARTICLE: Modeling and optimization for noise-aversion and energy-awareness disassembly sequence planning...

Area of Science:

• Operations Research
• Environmental Engineering
• Sustainable Manufacturing

Background:

• Reverse supply chain management is crucial for environmental protection and economic development.
• Disassembly is a key process in reverse logistics for component recovery and remanufacturing.
• Sustainable development necessitates efficient organization of remanufacturing processes.

Purpose of the Study:

• To address the stochastic disassembly sequence planning problem in reverse supply chains.
• To maximize disassembly profit while considering noise pollution and energy consumption.
• To develop a robust model and algorithm for sustainable remanufacturing.

Main Methods:

• Formulation of a chance-constrained programming model for mathematical description.
• Design of a discrete marine predators algorithm integrated with stochastic simulation.
• Conducting simulation experiments on real-life instances for validation.

Main Results:

• The proposed model and algorithm yield superior disassembly plans compared to existing methods.
• Maximal profit is achieved subject to noise pollution and energy consumption constraints.
• The approach effectively handles the complexities of stochastic disassembly planning.

Conclusions:

• The developed method provides an efficient and effective solution for sustainable disassembly processes.
• It contributes to achieving highly reliable and environmentally conscious remanufacturing.
• The approach supports informed decision-making in reverse supply chain management.