Simplified Swarm Optimization in efficient tool assignment of disassembly sequencing problem

The end-of-life (EOL) disassembly sequencing problem (DSP) has already become extremely important. We know that the parts, sub-components or raw materials in discarded EOL products are disassembled for reuse in the spirit of eco-friendliness. We also know that disassembly sequencing with adequate tool assignment would ameliorate the process in recycling, reclamation, or remanufacturing. Thus, this paper has investigated tool assignment in the context of DSPs, and formulates a tool-selected disassembly sequencing problem (TDSP) that considers both the tool assignment and disassembly sequence. This paper aims to minimize the disassembly time in the TDSP. In nature, the proposed TDSP is comparatively practical and reasonable to use in real-life applications, and is an NP-complete combinatorial optimization problem (COP). This paper proposes swarm-based soft computing with self-adaptive parameter control called Simplified Swarm Optimization (SSO) to solve this new COP. Based on the statistical significance testing, the experimental results have shown that the advanced SSO can solve the proposed TDSP efficiently and effectively in comparison with GA and PSO.