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2013•Applied Mechanics and MaterialsRequires access

The Simulated Annealing Algorithm Based on Multi-Populations Application of TSP

Qin Hui Gong

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Abstract

Traveling salesman problem (TSP) is not only a combinatorial optimization problem but also a classical NP problem, which has has high application value. Simulated annealing algorithm is especially effective for solving TSP problems. Based on the deficiency of simulated annealing algorithm on avoiding local minima, this paper has improved the traditional simulated annealing algorithm, proposed simulated annealing algorithm of multiple populations to solve the classical TSP problem. This algorithm has introduced collateral mechanism of multiple populations and increased the initial populations so that it can include more solution set, avoid local minima, thus it has improved the optimization efficiency.This algorithm has very high use value in solving the TSP problem. Keywords: Traveling salesman problem, NP (Non-deterministic Polynomial) problem, simulated annealing algorithm, multiple populations

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What this paper is about

Traveling salesman problem (TSP) is not only a combinatorial optimization problem but also a classical NP problem, which has has high application value. Simulated annealing algorithm is especially effective for solving TSP problems. Based on the deficiency of simulated annealing algorithm on avoiding local minima, this paper has improved the traditional simulated annealing algorithm, proposed simulated annealing algorithm of multiple populations to solve the classical TSP problem. This algorithm has introduced collateral mechanism of multiple populations and increased the initial populations so that it can include more solution set, avoid local minima, thus it has improved the optimization efficiency.This algorithm has very high use value in solving the TSP problem. Keywords: Traveling salesman problem, NP (Non-deterministic Polynomial) problem, simulated annealing algorithm, multiple populations

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Available abstract

Traveling salesman problem (TSP) is not only a combinatorial optimization problem but also a classical NP problem, which has has high application value. Simulated annealing algorithm is especially effective for solving TSP problems. Based on the deficiency of simulated annealing algorithm on avoiding local minima, this paper has improved the traditional simulated annealing algorithm, proposed simulated annealing algorithm of multiple populations to solve the classical TSP problem. This algorithm has introduced collateral mechanism of multiple populations and increased the initial populations so that it can include more solution set, avoid local minima, thus it has improved the optimization efficiency.This algorithm has very high use value in solving the TSP problem. Keywords: Traveling salesman problem, NP (Non-deterministic Polynomial) problem, simulated annealing algorithm, multiple populations

Key concepts: Simulated annealing, Travelling salesman problem, Maxima and minima, Mathematical optimization, Adaptive simulated annealing, Algorithm, Bottleneck traveling salesman problem, Computer science

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