Open AccessHybrid Algorithm for Solving Traveling Salesman Problem
Author(s) -
Ping Zhao,
Degang Xu
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/646/1/012032
Subject(s) - simulated annealing , travelling salesman problem , algorithm , hybrid algorithm (constraint satisfaction) , mathematical optimization , convergence (economics) , computer science , 2 opt , adaptive simulated annealing , genetic algorithm , process (computing) , mathematics , economic growth , stochastic programming , economics , constraint programming , constraint logic programming , operating system
The basic genetic algorithm has the disadvantages of falling into local optimum and slow convergence. To solve this problem, a hybrid algorithm combining simulated annealing strategy is proposed. The cooling process in simulated annealing is used to complete the iterative process in the hybrid algorithm. The algorithm is used to solve the traveling salesman problem. The results show that the convergence speed and accuracy of the hybrid algorithm is significantly better than the basic genetic algorithm.