Title: On mass effects to artificial physics optimisation algorithm for global optimisation problems

Authors: Liping Xie, Jianchao Zeng, Zhihua Cui

Addresses: College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, 730050, China; Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, No. 66 Waliu Road, Wanbailin District, Taiyuan, Shanxi, 030024, China. ' Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, No. 66 Waliu Road, Wanbailin District, Taiyuan, Shanxi, 030024, China. ' Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, No. 66 Waliu Road, Wanbailin District, Taiyuan, Shanxi, 030024, China

Abstract: Artificial physics optimisation (APO) algorithm is an optimisation algorithm based on physicomimetics framework. Driven by virtual force, a population of sample individuals searches a global optimum in the problem space. The mass of each individual corresponds to a user-defined function of the value of an objective function to be optimised. It is an important parameter to influence the performance of APO algorithm. Therefore, in this paper, the authors make a study on the selection principle of mass on numerical optimisation problems. According to the curvilinear style of the mass functions, they are classified into three different types of curvilinear functions: convex function, linear function and concave function. To make a deep insight, several versions of APO algorithm with different mass functions are used to solve two type benchmarks: unimodal and multimodal functions. Simulation results show the mass functions with concave curve may generally obtain the satisfied solution within the allowed iterations. In addition, the performance of APO algorithm is compared with that of the modified electromagnetism-like (EM), differential evolution (DE), evolutionary algorithm (EA) and particle swarm optimisation (PSO) for multidimensional numeric benchmarks. The simulation results show that APO algorithm is competitive.

Keywords: physicomimetics; artificial physics optimisation; APO; global optimisation; virtual force; Newton; second law; simulation.

DOI: 10.1504/IJICA.2009.031777

International Journal of Innovative Computing and Applications, 2009 Vol.2 No.2, pp.69 - 76

Available online: 24 Feb 2010

Full-text access for editors Access for subscribers Purchase this article Comment on this article