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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。
In order to solve the problem of the fuzzy configuration of complex products in mass customization mode, this paper proposes a product configuration fuzzy solution algorithm based on CBR and a product configuration optimization algorithm based on multi-objective genetic algorithm. The two algorithms are respectively corresponding to the components 'configuration and the parts' configuration in the process of product configuration, and the mathematical models for judging the similarity between the old configuration and the old configuration are designed. Based on the multi-objective genetic algorithm, the optimization model with cost, time and inventory is optimized Part configuration optimization solution algorithm, these two parts of the solution process to complete the product configuration solution. The algorithm effectively solves the problem of fuzzy data processing and configuration combination explosion in complex product configuration.