Solving the Euclidean Steiner Minimum Tree Using Cellular Stochastic Diffusion Search Algorithm

作     者：张瑾 赵雅靓 马良 ZHANG Jin 1,ZHAO Ya-liang 1,MA Liang 2(1.Institute of Image Processing and Pattern Recognition,Henan University,Kaifeng 475001,Henan,China;2.School of Management,University of Shanghai for Science and Technology,Shanghai 200093,China)

作者机构：Institute of Image Processing and Pattern RecognitionHenan University School of ManagementUniversity of Shanghai for Science and Technology 

出 版 物：《Journal of Shanghai Jiaotong university(Science)》 (上海交通大学学报（英文版）)

年 卷 期：2011年第16卷第6期

页      面：734-741页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0701[理学-数学] 

基　　金：the National Natural Science Foundation of China (No.70871081) the Science and Technology Department Research Project of Henan Province(No.112102310448) the Natural Science Foundation of Henan University (No.2010YBZR047) 

主　　题：Euclidean Steiner minimum tree stochastic diffusion search cellular automata 

摘      要：The Euclidean Steiner minimum tree problem is a classical NP-hard combinatorial optimization *** of the intrinsic characteristic of the hard computability,this problem cannot be solved accurately by efficient algorithms up to *** to the extensive applications in real world,it is quite important to find some heuristics for *** stochastic diffusion search algorithm is a newly population-based algorithm whose operating mechanism is quite different from ordinary intelligent algorithms,so this algorithm has its own advantage in solving some optimization *** paper has carefully studied the stochastic diffusion search algorithm and designed a cellular automata stochastic diffusion search algorithm for the Euclidean Steiner minimum tree problem which has low time *** results show that the proposed algorithm can find approving results in short time even for the large scale size,while exact algorithms need to cost several hours.