Ant algorithms for discrete optimization
Artificial Life
Future Generation Computer Systems
A Study of Some Properties of Ant-Q
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Team Algorithms Based on Ant Colony Optimization --- A New Multi-Objective Optimization Approach
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
A New Hybrid Ant Colony Optimization Algorithm for the Traveling Salesman Problem
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Mobile Robot Global Path Planning Based on Improved Augment Ant Colony Algorithm
WGEC '08 Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing
A Novel Cloud-Based Fuzzy Self-Adaptive Ant Colony System
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 07
A New Approach to Improve the Ant Colony System Performance: Learning Levels
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
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The ant colony algorithm (ACA) is a novel simulated evolutionary algorithm which is based on observations to behavior of some ant species Because of the use of positive feedback mechanism, ACA has stronger robustness, better distributed computer system and easier to combine with other algorithms However, it also has the flaws, for example mature and halting This paper presents an optimization algorithm by used of multi-population hierarchy evolution Each sub-population that is entrusted to different control achieves respectively a different search independently Then, for the purpose of sharing information, the outstanding individuals are migrated regularly between the populations The algorithm improves the parallelism and the ability of global optimization by the method At the same time, according to the convex hull theory in geometry, the crossing point of the path is eliminated Taking advantage of the common TSPLIB in international databases, lots of experiments are carried out It is verified that the optimization algorithm effectively improves the convergence rate and the accuracy of reconciliation.