A new hybrid heuristic approach for solving large traveling salesman problem
Information Sciences—Informatics and Computer Science: An International Journal
Particle swarm optimization-based algorithms for TSP and generalized TSP
Information Processing Letters
Simulated Annealing versus Metropolis for a TSP instance
Information Processing Letters
Improving inductive logic programming by using simulated annealing
Information Sciences: an International Journal
An analysis of the elastic net approach to the traveling salesman problem
Neural Computation
A simulated annealing algorithm for single machine scheduling problems with family setups
Computers and Operations Research
Information Sciences: an International Journal
Computers and Operations Research
A simulated annealing algorithm for determining the thickness of a graph
Information Sciences: an International Journal
Beam-ACO for the travelling salesman problem with time windows
Computers and Operations Research
A hybrid particle swarm optimization algorithm for the vehicle routing problem
Engineering Applications of Artificial Intelligence
A hybrid heuristic for the traveling salesman problem
IEEE Transactions on Evolutionary Computation
A Novel Constructive-Optimizer Neural Network for the Traveling Salesman Problem
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An annealing framework with learning memory
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A novel genetic algorithm based on immunity
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A modified ant colony system for solving the travelling salesman problem with time windows
Mathematical and Computer Modelling: An International Journal
Multi-agent simulated annealing algorithm based on differential evolution algorithm
International Journal of Bio-Inspired Computation
Solving the team orienteering problem using effective multi-start simulated annealing
Applied Soft Computing
Two-machine robotic cell scheduling problem with sequence-dependent setup times
Computers and Operations Research
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
A discrete gravitational search algorithm for solving combinatorial optimization problems
Information Sciences: an International Journal
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The traveling salesman problem (TSP) is a classical problem in discrete or combinatorial optimization and belongs to the NP-complete classes, which means that it may be require an infeasible processing time to be solved by an exhaustive search method, and therefore less expensive heuristics in respect to the processing time are commonly used in order to obtain satisfactory solutions in short running time. This paper proposes an effective local search algorithm based on simulated annealing and greedy search techniques to solve the TSP. In order to obtain more accuracy solutions, the proposed algorithm based on the standard simulated annealing algorithm adopts the combination of three kinds of mutations with different probabilities during its search. Then greedy search technique is used to speed up the convergence rate of the proposed algorithm. Finally, parameters such as cool coefficient of the temperature, the times of greedy search, and the times of compulsive accept and the probability of accept a new solution, are adaptive according to the size of the TSP instances. As a result, experimental results show that the proposed algorithm provides better compromise between CPU time and accuracy among some recent algorithms for the TSP.