Optimization Models and Heuristic Method Based on Simulated Annealing Strategy for Traveling Salesman Problem

Xu Hao

doi:10.4028/www.scientific.net/AMM.34-35.1180

Paper Titles

User’s Preference Aggregation Based on Parallel Interactive Genetic Algorithms
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Evaluation on Emergency Management System in Supply Chain Based on Trapezoidal Fuzzy Order Weighted Average (FOWA) Operator
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Empirical Study of the Influencing Factors of Supply Chain Risks
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Optimization Models and Heuristic Method Based on Simulated Annealing Strategy for Traveling Salesman Problem
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Financial Management of the Company for Financial Crisis
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E-Commerce Model Based on Grid Computing
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The Dynamic Balancing Performance of the Machinery Based on Virtual Prototyping Technology
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 34-35Optimization Models and Heuristic Method Based on...

Optimization Models and Heuristic Method Based on Simulated Annealing Strategy for Traveling Salesman Problem

Abstract:

The traveling salesman problem (TSP) is a problem in combinatorial optimization studied in operations research and theoretical computer science. In this paper, we presented a novel heuristic simulated annealing algorithm for solving TSP. The algorithm is fully operational in the genetic role of crossover operator, and mutation operator, to achieve a balance between speed and accuracy. The experiment results show that the algorithm is better than the traditional method.

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Periodical:

Applied Mechanics and Materials (Volumes 34-35)

Pages:

1180-1184

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.34-35.1180

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Online since:

October 2010

Authors:

Xu Hao

Keywords:

Combinatorial Optimization, Genetic Algorithm (GA), Simulated Annealing (SA), Traveling Salesman Problem (TSP)

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