Genetic-algorithm-based balanced distribution of functional characteristics for machines

In order to make reconfigurable manufacturing system (RMS) adapt to the fluctuations of production demand with the minimum number of reconfigurations in its full life cycle, we presented a method to design RMS based on the balanced distribution of functional characteristics for machines. With this method, functional characteristics were classified based on machining functions of cutting-tools and machining accuracy of machines. Then the optimization objective was set as the total shortest mobile distance that all the workpieces are moved from one machine to another, and an improved genetic algorithm (GA) was proposed to optimize the configuration. The elitist strategy was used to enhance the global optimization ability of GA, and excellent gene pool was designed to maintain the diversity of population. Software Matlab was used to realize the algorithm, and a case study of simulation was used to evaluate the method.