Paper Title:
A New Chaos Optimization Algorithm and its Application
  Abstract

In order to avoid blind searching before reducing the searching space of optimized variable and enhance searching efficiency in chaos optimization algorithm, a new mutative scale chaos optimization algorithm, Probability Chaos Optimization Algorithm (PCOA) was proposed. The current searching space is searched according to large probability and the origin space is searched according to small probability. Though the searching space is shrunk prematurely, the global optimal point can be found because the origin space is still searched according to small probability, which can overcome the shortcoming of losing the global optimal points owing to prematurely shrinking the searching space of the optimized variables in conventional mutative scale chaos optimization algorithm. The simulation results prove the validity of the algorithm.

  Info
Periodical
Key Engineering Materials (Volumes 439-440)
Edited by
Yanwen Wu
Pages
594-598
DOI
10.4028/www.scientific.net/KEM.439-440.594
Citation
L. F. Lu, C. B. Xiu, "A New Chaos Optimization Algorithm and its Application", Key Engineering Materials, Vols. 439-440, pp. 594-598, 2010
Online since
June 2010
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Tian Pei Zhou, Wen Fang Huang
Abstract:In the process of recycling chemical product in coking object, ammonia and tar were indispensable both metallurgy and agriculture, so the...
1945
Authors: Xiao Hua Wang, Yong Mei Zhang
Abstract:On the premise of ensuring safety and reliability in electricity market environment, the goal of State Grid Corporation is that purchase AGC...
274
Authors: Hui Qin Sun, Zhi Hong Xue, Ke Jun Sun, Su Zhi Wang, Yun Du
Chapter 2: Manufacturing Technology
Abstract:BP neural network is currently the most widely used of neural network models in practical application in transformer fault diagnosis. BP...
789
Authors: Si Lian Xie, Tie Bin Wu, Shui Ping Wu, Yun Lian Liu
Chapter 18: Computer Applications in Industry and Engineering
Abstract:Evolutionary algorithms are amongst the best known methods of solving difficult constrained optimization problems, for which traditional...
2846
Authors: Zi Xu, Jing Yu
Chapter 6: Computational Simulation, Monitoring and Analysis in Manufacture
Abstract:This paper proposes the combined direction stochastic approximation method for solving simulation-based optimization problems. The new...
688