  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.
