Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous Abstract"Volatile organic compound (VOC) adsorption on material: influence of gas phase concentration, relative humidity and VOC type"    Next AbstractTerpene Synthase-b and Terpene Synthase-e/f Genes Produce Monoterpenes for Phalaenopsis bellina Floral Scent »

IEEE Trans Syst Man Cybern B Cybern


Title:A pheromone-rate-based analysis on the convergence time of ACO algorithm
Author(s):Huang H; Wu CG; Hao ZF;
Address:"School of Software Engineering, South China University of Technology, Guangzhou 510006, China. hhan@scut.edu.cn"
Journal Title:IEEE Trans Syst Man Cybern B Cybern
Year:2009
Volume:20090417
Issue:4
Page Number:910 - 923
DOI: 10.1109/TSMCB.2009.2012867
ISSN/ISBN:1941-0492 (Electronic) 1083-4419 (Linking)
Abstract:"Ant colony optimization (ACO) has widely been applied to solve combinatorial optimization problems in recent years. There are few studies, however, on its convergence time, which reflects how many iteration times ACO algorithms spend in converging to the optimal solution. Based on the absorbing Markov chain model, we analyze the ACO convergence time in this paper. First, we present a general result for the estimation of convergence time to reveal the relationship between convergence time and pheromone rate. This general result is then extended to a two-step analysis of the convergence time, which includes the following: 1) the iteration time that the pheromone rate spends on reaching the objective value and 2) the convergence time that is calculated with the objective pheromone rate in expectation. Furthermore, four brief ACO algorithms are investigated by using the proposed theoretical results as case studies. Finally, the conclusions of the case studies that the pheromone rate and its deviation determine the expected convergence time are numerically verified with the experiment results of four one-ant ACO algorithms and four ten-ant ACO algorithms"
Keywords:"*Algorithms Animals Ants/*physiology Cybernetics/*methods *Markov Chains Models, Biological Models, Statistical Pheromones/*physiology;"
Notes:"MedlineHuang, Han Wu, Chun-Guo Hao, Zhi-Feng eng Research Support, Non-U.S. Gov't 2009/04/22 IEEE Trans Syst Man Cybern B Cybern. 2009 Aug; 39(4):910-23. doi: 10.1109/TSMCB.2009.2012867. Epub 2009 Apr 17"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 17-11-2024