Multi-objective low-carbon disassembly line balancing for agricultural machinery using MDFOA and fuzzy AHP

The issue of disassembly line balancing and remanufacturing has become an increasingly hot topic recently. However, little research focusing on carbon dioxide reduction and resource utilization has been done in the field of disassembly line balancing. For the purpose of being environmentally friendly, the disassembly line balancing should aim at low carbon emission, low energy consumption and cost reduction during the disassembly process. Considering this, this study proposes a multi-objective disassembly line balancing fruit fly optimization algorithm (MDFOA) for the disassembly sequence of obsolete agricultural machinery considering low-carbon design. We try to optimize the disassembly line balancing model using the fruit fly optimization algorithm. To satisfy the stability of MDFOA, the olfactory operation is cross-operated, and the Pareto non-dominated sorting method is adopted in the visual operation stage. In order to avoid falling into local optimum, a global cooperation mechanism is added to screen individuals with different degrees of dissimilarity. An illustrative example of the disassembly line of corn harvester cutting table is provided in this work. Comparison between our proposed MDFOA and other four frequently-used algorithms is conducted in this work. The results show that our method performs better than other algorithms for the disassembly line balancing problem (DLBP), thus verifying the practicability and feasibility of it. In the end, 12 Pareto solutions are obtained through MDFOA and we evaluated and selected the most satisfactory solution among them using Fuzzy AHP, for the determination of the optimal disassembly sequence. (C) 2019 Elsevier Ltd. All rights reserved.