CACO : Competitive Ant Colony Optimization, A Nature-Inspired Metaheuristic For Large-Scale Global Optimization
Neural and Evolutionary Computing
2013-12-17 v1
Abstract
Large-scale problems are nonlinear problems that need metaheuristics, or global optimization algorithms. This paper reviews nature-inspired metaheuristics, then it introduces a framework named Competitive Ant Colony Optimization inspired by the chemical communications among insects. Then a case study is presented to investigate the proposed framework for large-scale global optimization.
Cite
@article{arxiv.1312.4044,
title = {CACO : Competitive Ant Colony Optimization, A Nature-Inspired Metaheuristic For Large-Scale Global Optimization},
author = {M. A. El-Dosuky},
journal= {arXiv preprint arXiv:1312.4044},
year = {2013}
}