Assembly Sequence Planning Based on Max-Min Ant Colony System

An assembly sequence planning (ASP) method that combined the advantages of ant colony system (ACS) and Max-Min ant system (MMAS) is proposed. To identify the best sequence easily, five optimization criterions are automatically quantified, including reorientation, parallelism, continuity, stability and auxiliary stroke, and then integrated into the multi-objective heuristic and fitness functions of ant colony optimization (ACO). To improve the search capability for the global-best sequence, several measures are presented from aspects of determining number of ant, max-min pheromone limits, performance appraisal for initial components allocation and the group method for same components. The ASP algorithm based on Max-Min ant colony system (MMACS) is proposed. An assembly planning system AutoAssem is developed based on Siemens NX platform, and the actual effectiveness of each optimization measure is testified through case study of a valve.