Open AccessSolving TSP based on an Improved Ant Colony Optimization Algorithm
Author(s) -
Hao Zhang,
Yahui Gao
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1982/1/012061
Subject(s) - travelling salesman problem , ant colony optimization algorithms , mathematical optimization , heuristic , metaheuristic , computer science , parallel metaheuristic , ant colony , extremal optimization , population , field (mathematics) , algorithm , mathematics , meta optimization , demography , sociology , pure mathematics
Traveling Salesman Problem (TSP) is a typical Problem in combinatorial optimization field in modern times. Most of the problems in reality can be transformed into TSP problems for solving. Such as postal problems, communication network design, etc. Ant colony algorithm, as a heuristic algorithm, has been successfully applied to solving TSP problems. Based on the improved ant colony algorithm, this paper solves the travel agent problem, evaluates the population according to the membership degree, and updates the pheromone in turn, so as to achieve a good balance in solving speed and quality.