Fitting of an Ant Colony approach to Dynamic Optimization through a new set of test functions

Real world problems are often of dynamic nature. They form a class of difficult problems that metaheuristics aim to solve. The goal is not only to attempt to find near-to optimal solutions for a defined objective function, but also to track them in the search space. We will discuss in this article the dynamic optimization in the continuous case. Then we will present the experimentation on a battery of test functions, specially tuned for that purpose, of our ant colony algorithm, DHCIAC (Dynamic Hybrid Continuous Interacting Ant Colony).