A Particle Swarm Optimization Approach to A Multi-objective Reconfigurable Machine Tool Design Problem

The design of reconfigurable machine tools (RMTs) involves three criteria: configurability, cost and process accuracy with preferred priority order. This paper presents a modified fuzzy Chebyshev programming (MFCP) approach to achieving the best compromise of the three design objectives without violating their priority order. A mechanism is developed to automatically generate and evaluate alternative designs. A particle swarm optimization algorithm (PSOA) is applied to provide quick and near optimal solutions for large design problems. The application of the proposed multi-objective design approach is demonstrated using a reconfigurable boring machine. Our computational experience has shown that the PSOA method is efficient and robust.