文献类型：期刊文献

英文题名：CRYSTAL ENERGY OPTIMIZATION ALGORITHM

作者：Feng, Xiang[1];Ma, Meiyi[1];Yu, Huiqun[1]

机构：[1]East China Univ Sci & Technol, Dept Comp Sci & Engn, Meilong Rd 130, Shanghai 200237, Peoples R China

年份：2016

卷号：32

期号：2

起止页码：284

外文期刊名：COMPUTATIONAL INTELLIGENCE

收录：;EI(收录号：20161902368359);WOS:【SCI-EXPANDED(收录号:WOS:000383364200006)】；

基金：This work was supported in part by the National Natural Science Foundation of China under grant nos. 60905043, 61073107, and 61173048, the Innovation Program of Shanghai Municipal Education Commission, and the Fundamental Research Funds for the Central Universities.

语种：英文

外文关键词：crystal energy optimizer (CEO); computational intelligence; parallel algorithm; nature-inspired algorithm; traveling salesman problem (TSP)

摘要：Nature has always been a muse for those who dream in art or science. As it goes, optimization algorithms inspired by nature have been widely used to solve various scientific and engineering problems because of their intelligence and simplicity. As a novel nature-inspired algorithm, the crystal energy optimizer (CEO) is proposed in this article. The proposed CEO is motivated by the following general observation on lake freezing in nature: the dynamics of crystals have possession of parallelism, openness, local interactivity, and self-organization. It stimulates us to extend a crystal dynamic model in physics to a generalized crystal energy optimizer for traveling salesman problems, so as to exploit the advantages of crystal dynamic system and to realize the aforementioned purposes. The proposed CEO has these advantages: (1) it has the ability to perform large-scale distributed parallel optimization; (2) it can converge and avoid local optimum; and (3) it is flexible and easy to adapt to a wide range of optimization problems.