A Multiobjective Disassembly Planning for Value Recovery and Energy Conservation From End-of-Life Products

摘要: Demanufacturing aims to recover value and conserve energy from end-of-life (EOL) products, contributing sustainable manufacturing. To make the full use of EOL they are usually disassembled into components that have different values embodied at options. This article studies a disassembly planning (DP) integrates decisions on sequence strategy maximize recovered conservation products. We propose multiobjective DP based recovery (MDPVE) model, which is existing models by focusing rather than consumption during disassembly. An adapted artificial bee colony (ABC) algorithm [multiobjective ABC (MOABC)] developed identify Pareto solutions for MDPVE compared with well-known metaheuristic algorithm, Non-dominated Sorting Genetic Algorithm-II (NSGA-II). A real-world case study demonstrated superior solution quality computational efficiency MOABC. Note Practitioners —There often more one treatment option products or components, including reuse, remanufacturing, recycling. However, decision select not considered in most assuming an given each component. Hence, plan focused this article. As sustainability gains increasing attention, it essential assess profitability simultaneously Since there could be tradeoff between profit conserved energy, evolutionary generating help decision-makers find good both evaluation indicators.