摘要
基于可信性理论和两阶段模糊优化方法,提出一类新的带有最小风险准则的两阶段模糊运输模型。由于提出的模糊运输问题包含带有无限支撑的模糊变量参数,因此它是一个无限维的优化问题。为了求解这个模糊优化问题,这里将讨论两阶段模糊运输问题的逼近方法并且将逼近方法嵌套到遗传算法中产生一个基于遗传算法的混合智能算法求解提出的带有最小风险准则的两阶段模糊运输问题。给出一个数值例子来表明所设计模型和算法的实用性。
Based on credibility theory and two-stage fuzzy optimization method,this paper presents a new class of two-stage fuzzy transportation model with minimum risk criteria.Since the proposed transportation peoblem includes fuzzy variable parameters with infinite supports in this paper, it is infinite-dimensional optimization problem.In order to solve this fuzzy programming problem, the approximation approach of two-stage fuzzy transportation problem is discussed and embeded into a genetic algorithm to produce hybrid algorithm for solving the proposed two-stage fuzzy transportation problem with minimum risk criteria.A numerical example is given to show the practicality of the designed model and algorithm.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第35期63-66,共4页
Computer Engineering and Applications
基金
河北省高等学校自然科学研究青年基金项目(No.2010124)
河北省自然科学基金(No.A2008000563)
关键词
运输问题
两阶段模糊优化
逼近方法
最小风险准则
遗传算法
transportation problem
two-stage fuzzy optimization
approximation approach
mini＇mum risk criteria
genetic algorithm
