CACO : Competitive Ant Colony Optimization, A Nature-Inspired Metaheuristic For Large-Scale Global Optimization
This addresses optimization challenges for researchers and practitioners dealing with large-scale nonlinear problems, but appears incremental as it builds on existing ant colony optimization methods.
The paper tackles large-scale global optimization by introducing Competitive Ant Colony Optimization, a nature-inspired metaheuristic framework based on insect chemical communications, and presents a case study to investigate its performance.
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.