产品配置的模糊求解及优化算法研究

Fuzzy Solution and Optimization of Product Configuration

为了解决大规模定制生产模式下复杂产品模糊配置的求解问题,提出了以基于实例推理技术(CBR)为基础的产品配置模糊求解算法,及基于多目标遗传算法的产品配置优化算法。两算法分别对应于产品配置过程中的部件配置与零件配置的求解内容,设计了判断新旧配置实例相似度的数学模型,并基于多目标遗传算法求解以成本、时间和库存为多个优化目标的零件配置优化求解算法,这2部分求解过程共同完成产品配置求解。该算法有效地解决了复杂产品配置中模糊数据处理及配置组合爆炸的问题。

For dealing with the fuzzy configuration problem of complicated product in the new mass customization environment, a Case-based Reasoning （CBR） based fuzzy solution of product configuration was proposed, and a configuration optimization method based on multi-objective genetic algorithm was designed. These two algorithms were used for solving subassemblies configuration and parts configuration respectively. The mathematic model for calculating the similarity of the new and old case was designed. The multi-objective genetic algorithm was applied for solving the multi-objective optimization of the parts configuration, and the cost, time and inventory were the three optimal objectives. These two configuration procedures together completed the product configuration. This new algorithm solved the fuzzy data processing and combinatorial explosion problems of complicated product configuration.