Rapid Configuration of Reconfigurable Manufacturing Systems Based on Improved Genetic Algorithms
A multi-objective optimization method is proposed for the rapid configuration of reconfigurable manufacturing systems,considering three optimization objectives:equipment load balance,product production time,and product production cost.A multi-objective genetic-neighborhood search algorithm(NSGA-NS)is constructed based on the third generation multi-objective genetic algorithm-Ⅲ(NSGA-Ⅲ)combined with neighborhood search to find a series of front solutions from the configuration solution space.The algorithm is validated by a configuration case of a hydraulic valve block manufacturing system,and compared with the ar-chived multi-objective simulated annealing,multi-objective particle swarm optimization,and an improved multi-objective particle swarm optimization.The results show that NSGA-NS and NSGA-Ⅲsignificantly out-perform each other in terms of front solutions quality,NSGA-NS significantly improves the convergence speed and calculational speed while maintaining the global search performance of NSGA-Ⅲ.
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