摘要
针对汽车零部件企业供应商选择周期长、供应商数目较多、评价指标繁多、流程复杂、评判要求异常严格的特点,建立了适用于汽车零部件企业的供应商选择双层规划模型,该模型从采购商和供应商的不同角度,对选择目标进行分解,通过上下层目标函数综合评价多种选择因子,得到最优供应商选择方案,以使采购总费用最小,产品质量最好。在模型中平衡和优化供应商与采购商双方利益,考虑了供应商的技术、质量、价格、供货能力和服务等多个约束条件;设计了模型的遗传算法求解算法,并用实例验证了模型和算法的有效性和实用性,为汽车零部件企业的供应商选择提供了有价值的参考。
Focusing on the characteristics of automobile components industry, such as long-term supplier selection, large number of suppliers, various assessment index, complicated processes, and extremely strict assessment requirements, an improved supplier selection bilevel programming model for automobile components industry is established. With this model, the authors analyzed selected objectives from viewpoints of both suppliers and purchasers, assessed several selectied factors with upper and lower layer objective functions, and produced a optimal supplier selection method to achieve minimum purchasing costs. This model takes several constraints, such as technology, quality, quoted price, supply capacity and services of suppliers, into consideration, which makes the model very practical. A genetic-algorithms-based calculation method is designed, and the model is validated through a case study. Both the model and the method provide valuable support to supplier selection in the automobile components industry.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2007年第7期10-13,17,共5页
Journal of Chongqing University
基金
重庆市科技攻关项目(2004-8364)
关键词
供应商选择
双层规划
遗传算法
汽车零部件
supplier selection
bilevel programming
genetic algorithms
automobile component
