A global optimization based on physicomimetics framework

Authors:
Li-Ping Xie;Jian-Chao Zeng
Affiliations:
Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, Taiyuan,ShanXi, China;Complex System and Computational Intelligence Laboratory, Taiyuan,ShanXi, China
Venue:
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Year:
2009

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Abstract

Based on physicomimetics framework, this paper presents a global optimization algorithm inspired by physics, which is a stochastic population-based algorithm. In the approach, each physical individual has a position and velocity which move through the feasible region of global optimization problem under the influence of gravity. The virtual mass of each individual corresponds to a user-defined function of the value of an objective function to be optimized. An attraction-repulsion rule is constructed among individuals and utilized to move individuals towards the optimality. Experimental simulations show that the algorithm is effective.