Partheno Genetic Ant Colony Optimization Algorithm and its Application

Guo Li Wang; Jian Hui Wu; Yu Su

doi:10.4028/www.scientific.net/AMR.143-144.1132

Paper Titles

The Effect of Temperature and Oxide Concentration of Galena Oxidation
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Comparative Analysis of Three General Game Players
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Improved Iterative Methods for Solving High Order Polynomial Equations
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The Study of the Factors to Establishing an Online Environment for Negotiation
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Partheno Genetic Ant Colony Optimization Algorithm and its Application
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Prediction for the Sulfur Content in Pig Iron of Blast Furnace by Combining Artificial Neural Network with Genetic Algorithm
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Four Quadrants Numerical Prediction for Hydrodynamic Performance of Open-Water Propeller
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On the Convergence of Parallel Broyden Method
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An Improved PSO-ACO Algorithm for Solving Large-Scale TSP
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 143-144Partheno Genetic Ant Colony Optimization Algorithm...

Partheno Genetic Ant Colony Optimization Algorithm and its Application

Abstract:

Ant colony algorithm is a kind of effective combinatorial optimization problem solving algorithm has been increasingly, thorough research, and gradually get used. Ant colony algorithm is a set of parameters, the algorithm, a lack of adequate experiences often. The paper has put forward a single genetic character of ant colony algorithm. Will the ant colony algorithm each search results as the initial population, single genetic improvement, for the shortest route optimization. In the traveling salesman problem of the experiments prove the effectiveness of the proposed algorithm.

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Periodical:

Advanced Materials Research (Volumes 143-144)

Pages:

1132-1136

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.143-144.1132

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Online since:

October 2010

Authors:

Guo Li Wang, Jian Hui Wu, Yu Su

Keywords:

Dichotomy Method, Iterative Method, Newton Iteration Method, Real Root, Sturm Sequence

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