随机规划ICC(β)模型的混合智能算法  

On Integrated Chance Constraints Model of Stochastic Program

作　　者：戎晓霞[1] 刘家壮[1] 

机构地区：[1]山东大学数学与系统科学学院,济南250100

出　　处：《计算机工程与应用》2005年第11期12-14,共3页Computer Engineering and Applications

基　　金：国家科技攻关计划(编号:2002BA404A11)

摘　　要：讨论了当随机规划的随机变量服从离散分布时,合成机会约束模型(ICC(β))中约束集合的结构;利用适合全局搜索的遗传算法以及局部搜索能力很强的爬山算法,结合逐次增加约束方法,给出了计算该模型的混合智能算法;实例验证了该算法的有效性。该算法也可作为含连续随机变量的(ICC(β))的逼近算法。In this paper,the property of feasible solution set in ICC(β)is discussed assuming that the random variables of(SP)are discrete;Based on an integrated genetic algorithm with hill climbing and the method of adding constraints,a hybrid algorithm is given.Experiments show that this algorithm is efficient compared with that of 3,and it can also be an approach algorithm for ICC(β)with continuous random variable.

关 键 词：随机规划 合成机会约束 遗传算法 爬山算法 

分 类 号：O221.5[理学—运筹学与控制论] C931[理学—数学]