关键词: 供应商选择, 质量控制, 成本控制, 集对分析, 不确定分析, 演化细胞学习自动机, 模糊集值统计

Abstract: To study influence of uncertain information on product quality & cost control process with suppliers'involvement, Set Pair Analysis (SPA) was adopted to build the multi-objective relative degree of nearness optimization model for quality & cost control. Evolutionary cellular learning automata algorithm was adaptively improved to solve the optimization model, and then quality & cost control alternatives set's priority ordering, i.e. basic ordering, was acquired under the relatively certain condition. Considering uncertain influences, fuzzy-set-valued statistics was utilized to obtain discrepancy degree coefficient Δ, therefore the basic ordering was reordered in the light of relation coefficient, and the optimal product quality & cost control concept alternative was selected. According to that optimal alternative, reasonable supplier was selected for each component. Finally, large scale deep cooling air-separating equipment's quality & cost control process as a practical case was provided to illustrate the application and validation of the proposed method by simulation and computation.

Key words: supplier selection, quality control, cost control, set pair analysis, uncertainty analysis, evolutionary cellular learning automata, fuzzy-set-valued statistics