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۱Evolutionary Algorithm for Extremal Subsets Comprehension in Graphs
اطلاعات انتشار: World Applied Sciences Journal، بيست و هفتم،شماره۹، ۲۰۱۳، سال
تعداد صفحات: ۶
This article deals with the development and study of two–level evolutionary algorithm, as well as the experimental studies of its performance when solving NP–complete optimization problems of different extremal subsets comprehension in graphs. A new approach to the problem decision, based on a combined use of the genetic search principles and evolutionary modeling, as well as heuristic search methods are presented. A number of new modifications of knowledge–based genetic operators are developed. An original two–level search strategy for quasioptimal decisions, based on the intrafamilial and interfamilial exchanges, is proposed. The time complexity of the algorithm and the experimental results are presented. The most optimal algorithm parameters and settings, allowing one to obtain the best result, are shown. Conducted computational experiment allows us to refine the theoretical estimates of the proposed algorithm time complexity. The algorithm parameter points and settings, allowing us to obtain the best results, are presented. The time complexity of the developed algorithm is on average O(n2).
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