动态联盟中伙伴选择问题的区间规划模型及其求解

伙伴选择和风险管理是动态联盟中的重要决策问题,当考虑失败风险时,失败概率无法给出精确值,因此,考虑采用不确定性规划描述此类问题.提出动态联盟中伙伴选择问题的区间规划模型,模型中用区间数表示联盟伙伴的失败概率.为了求解该模型,引入序关系,并利用Nakahara和Ishibuchi的定理,将区间规划模型转化为等价的清晰双目标模型.设计带自适应适值函数的遗传算法,求出问题的全部非劣解.经过对多个问题的仿真,证明了算法的有效性.

Interval Programming Model of Partner Selection Problem in Virtual Enterprise and Its Solution

Partner selection and risk management are important decision problems in virtual enterprise.In some cases,failure probability cannot be given precisely,it is reasonable to denote this type of problem by uncertain programming.An interval programming model for partner selection is presented,in which members' failure probabilities are treated as interval coefficients.This model is transformed into equivalent bi-objective precise model by the definition of order relation between interval numbers and the theorem proved by Nakahara and Ishibuchi.A genetic algorithm with self-adaptive fitness function is proposed to find all Pareto solutions.Simulation results show that this approach is efficient.