Discrete particle swarm optimization for disassembly sequence planning

Due to government regulations, customer preferences, and cooperate finance interest, End-of-life (EOL) processing of products is becoming increasingly desirable. Reusing, recycling, remanufacturing, and disposing are choices for its processing. Most of all alternatives, disassembly may be needed. However, the disassembly process is a relatively expensive process due to its labor-intensive nature. Consequently, finding an optimal or near optimal disassembly sequence is desirable. This report presents a method of using discrete particle swarm optimization (PSO) for solving disassembly sequencing problem. The idea of applying PSO for a combinatorial optimization problem is proposed. Additionally, a dynamic precedence matrix for coping precedence constraints is presented. The test results show that the proposed method is effective and efficient for solving the disassembly sequencing problem.