GAACO: A GA + ACO Hybrid for Faster and Better Search Capability-Reference-Cited by-同舟云学术

GAACO: A GA + ACO Hybrid for Faster and Better Search Capability

Published:2002 Issue: Volume: Page:300-301
ISSN:0302-9743
Container-title:Ant Algorithms
language:
Short-container-title:

Author:

Acan Adnan

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-45724-0_35

Reference3 articles.

1. Stützle, T., Dorigo, M.: ACO Algorithms for the Traveling Salesman Problem. In: Miettinen, K., Neittaanmaki, P., Periaux, J. (eds.): Evolutionary Algorithms in Engineering and Computer Science, John Wiley & Sons (1999).

2. Stützle, T., Dorigo, M.: ACO Algorithms for the Quadratic Assignment Problem. In: Corne, D., Dorigo, M., Glover, F. (eds.): New Ideas in Optimization, McGraw-Hill, (1999).

3. Maniezzo, V., Colorni, A.: The Ant System Applied to the Quadratic Assignment Problem. IEEE Transactions on Knowledge and Data Engineering, (1999).

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Combining Edge Recombination Crossover with Ant Colony Optimisation for Improved Routing;Lecture Notes in Networks and Systems;2022-09-01

2. Application of GA-ACO Algorithm in Thin Slab Continuous Casting Breakout Prediction;Transactions of the Indian Institute of Metals;2022-08-27

3. Accelerating genetic algorithm evolution via ant-based mutation and crossover for application to large-scale TSPs;Proceedings of the Genetic and Evolutionary Computation Conference Companion;2022-07-09

4. A Greedy Approach to Ant Colony Optimisation Inspired Mutation for Permutation Type Problems;2021 IEEE Symposium Series on Computational Intelligence (SSCI);2021-12-05

5. ACO Inspired GA Mutation Applied to the TSP;Advances in Intelligent Systems and Computing;2021-11-18