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2010•Applied Mechanics and MaterialsRequires access

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

Hao Xu

Open publisher page 3 citations

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.

About this research paper

What this paper is about

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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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available 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.

Key concepts: Travelling salesman problem, Crossover, Simulated annealing, Mathematical optimization, 2-opt, Heuristic, Operator (biology), Bottleneck traveling salesman problem

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