Applying Improved Particle Swarm Optimization to Asynchronous Parallel Disassembly Planning

Disassembly Planning (DP) refers to an optimization method find the most cost-effective disassembly sequence for products based on properties of parts. In traditional sequential planning, only a single part or component is removed. To effectively improve product efficiency, this study explores problem Asynchronous Parallel (aPDP) with multiple manipulators. aPDP situation where manipulators are used, arranging needs be considered in addition limitation priority order This proposes improved particle swarm discuss combination problem. The minimum Make Span objective, and solution status convergence speed compared results other methods, Genetic Algorithm Ant Colony Optimization. show that proposed version algorithm has better quality execution time.