학술논문

An Improved Artificial Bee Colony with Self-Adaptive Strategies and Application
Document Type
Conference
Source
2021 International Conference on Computer Network, Electronic and Automation (ICCNEA) ICCNEA Computer Network, Electronic and Automation (ICCNEA), 2021 International Conference on. :101-104 Sep, 2021
Subject
Computing and Processing
Automation
Traveling salesman problems
Artificial bee colony algorithm
Computer networks
Particle swarm optimization
Optimization
Convergence
Artificial Bee Colony Algorithm
Self-adaptive Strategies
Improved
the Traveling Salesman Problem
Language
Abstract
Artificial bee colony algorithm (ABC) has been becoming a hot topic of swarm intelligence. Artificial bee colony algorithm shows great advantages in solving path problems. There still exist some shortcomings in basic ABC algorithm, such as low convergence rate and easily falling into local optimization. Hence, an improved Artificial Bee Colony algorithm is proposed in this paper. In the improved Artificial Bee Colony, self-adaptive strategies for updating food source is introduced to ensure time and accuracy of algorithm. The proposed algorithm is also applied to the traveling salesman problem. Experiments show the effectiveness of improved algorithm.