Continuous interacting ant colony algorithm based on dense heterarchy

Ant colony algorithms are a class of metaheuristics which are inspired from the behavior of real ants. The original idea consisted in simulating the stigmergic communication, therefore these algorithms are considered as a form of adaptive memory programming. A new formalization is proposed for the design of ant colony algorithms, introducing the biological notions of heterarchy and communication channels. We are interested in the way ant colonies handle the information. According to these issues, a heterarchical algorithm called “Continuous Interacting Ant Colony” (CIAC) is designed for the optimization of multiminima continuous functions. CIAC uses two communication channels showing the properties of trail and direct communications. CIAC presents interesting emergent properties as it was shown through some analytical test functions. © 2003 Elsevier B.V. All rights reserved.