An Effective Optimization Method Based on the Genetic Algorithm to Solve TSP

Xi Tao Hu; Jun  Huang; Shun Xiang  Wu

doi:10.4028/www.scientific.net/AMM.380-384.1454

Paper Titles

On the Positive Definite Solutions of a Nonlinear Matrix Equation
p.1434

The Mixed-Restriction Solution and its Application in Augmented Reality
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An Improved Niche Genetic Algorithm
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The Symmetrical Least Square Method on Zero-Crossing Linear Fitting
p.1448

An Effective Optimization Method Based on the Genetic Algorithm to Solve TSP
p.1454

A Knowledge Rule Mining Method for the Evaluation of Library Readers Satisfaction Rate
p.1460

Improved Genetic Algorithms for Software Testing Cases Generation
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Partition Real Data in Decision Tree Using Statistical Criterion
p.1469

The Application of Simulation Technology in the Inventory System
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 380-384An Effective Optimization Method Based on the...

An Effective Optimization Method Based on the Genetic Algorithm to Solve TSP

Abstract:

The Traveling Salesman Problem is one of the most intensively studied problems in computational mathematics. Due to the basic genetic algorithm convergence speed is slow, easy to stagnation. We present in this paper a new improved mutation strategy to solve this problem. Roulette wheel selection strategy is used to avoid running into trap of the part best value. And simulated niche method is introduced to accelerate the search process effetively. This algorithm has been checked on a set of 144 cities in China and it outperforms the results obtained with other TSP heuristic methods.

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Periodical:

Applied Mechanics and Materials (Volumes 380-384)

Pages:

1454-1459

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.380-384.1454

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Online since:

August 2013

Authors:

Xi Tao Hu, Jun Huang, Shun Xiang Wu

Keywords:

Genetic Algorithm (GA), Roulette Wheel Selection Strategy, Simulated Niche, TSP

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