By Topic

Using artificial physics to solve global optimization problems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Liping Xie ; College of Electrical and Information Engineering, Lanzhou University of Technology, China ; Jianchao Zeng ; Zhihua Cui

Heuristics are quite an effective kind of methods to solve global optimization problems, which utilizes sample solution(s) searching the feasible regions of the problems in various intelligent ways. Inspired by physical rule, this paper proposes a stochastic global optimization algorithm based on physicomimetics framework. In the algorithm, a population of sample individuals search a global optimum in the problem space driven by virtual forces, which simulate the process of the system continually evolving from initial higher potential energy to lower one until a minimum is reached. Each individual has a mass, position and velocity. The 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 and used to move individuals towards the optimality. Experimental simulations show that the algorithm is effective.

Published in:

Cognitive Informatics, 2009. ICCI '09. 8th IEEE International Conference on

Date of Conference:

15-17 June 2009