An Improved Ant Colony Optimization Algorithm Based on Hybrid Strategies for Scheduling Problem
Dalian Jiaotong University · Civil Aviation University of China
Abstract
In this paper, an improved ant colony optimization (ICMPACO) algorithm based on the multi-population strategy, co-evolution mechanism, pheromone updating strategy, and pheromone diffusion mechanism is proposed to balance the convergence speed and solution diversity, and improve the optimization performance in solving the large-scale optimization problem. In the proposed ICMPACO algorithm, the optimization problem is divided into several sub-problems and the ants in the population are divided into elite ants and common ants in order to improve the convergence rate, and avoid to fall into the local optimum value. The pheromone updating strategy is used to improve optimization ability. The pheromone diffusion…
Citation impact
- FWCI
- 57.47
- Percentile
- 100%
- References
- 82
Authors
3Topics & keywords
- Ant colony optimization algorithms
- Mathematical optimization
- Computer science
- Optimization problem
- Convergence (economics)
- Population
- Algorithm
- Mathematics