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Decentralized two-level 0-1 programming through genetic algorithms with double strings

机译:通过双字符串遗传算法进行去中心化的二级0-1编程

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We consider two-level programming problems in which there are one decision maker (the leader) at the upper level and two or more decision makers (the followers) at the lower level and decision variables of the leader and the followers are 0-1 variables. We assume that there is coordination among the followers while between the leader and the group of all the followers, there is no motivation to cooperate each other, and fuzzy goals for objective functions of the leader and followers are introduced in order to take fuzziness of their judgments into consideration. The leader maximizes the degree of satisfaction and the followers choose in concert so as to maximize a minimum among their degrees of satisfaction. A computational method, which is based on the genetic algorithms, for obtaining a solution to the above mentioned problem is developed. To demonstrate the feasibility and efficiency of the proposed algorithm, numerical experiments are carried out.
机译:我们考虑两级编程问题,其中上级有一个决策者(领导者),下级有两个或更多决策者(跟随者),而领导者和跟随者的决策变量是0-1变量。我们假设跟随者之间存在协调,而领导者和所有跟随者之间则没有动力,彼此之间没有合作的动机,并且引入了领导者和跟随者目标功能的模糊目标,以使他们的模糊性判断考虑在内。领导者最大化满意度,追随者一致选择,以使满意度最小。开发了一种基于遗传算法的计算方法,用于获得上述问题的解决方案。为了证明该算法的可行性和有效性,进行了数值实验。

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