摘要
讨论了定性和定量相结合选择动态联盟伙伴的问题,针对权系数信息不完全和指标值不确定提出了一种基于证据推理的优化模型。该模型首先通过证据推理算法将方案的指标值集结,然后将效用值集结,结合不完全信息的权系数建立非线性规划模型,设计了遗传算法来求解,从而选出最满意的伙伴。最后以实例表明该模型的有效性。
We present a qualitative and quantitative solution to select collaborating partners when establishing agile virtual enterprises. An optimization model is proposed, in which the information of all criteria＇ weights is incomplete and the criteria＇ values are uncertain. Through evidential reasoning algorithms, the criteria＇ values are aggregated. After aggregating the utility, a nonlinear programming model is developed combining with the incomplete information on weights. Then using genetic algorithms to solve the nonlinear model, the satisfactory partner is selected. Finally, an example is given to illustrate the model＇s validity.
出处
《运筹与管理》
CSCD
2006年第6期8-13,共6页
Operations Research and Management Science
基金
国家自然科学基金资助项目(70471042)
关键词
运筹学
动态联盟
证据推理
遗传算法
operations research
agile virtual enterprise
evidential reasoning
GA
