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ACO Modeling: Organizational Modeling of an Ant Multi-Colonies Optimization Approach
Author(s) -
Elie TagneFute,
Emmanuel Tonyé
Publication year - 2015
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/19859-1824
Subject(s) - computer science , ant colony optimization algorithms , ant , ant colony , operations research , artificial intelligence , data science , industrial engineering , operating system , engineering
This paper describes the organizational modeling of the Ant Colony Optimization (ACO). It presents a modeling approach of the ACO based on Holonic Multi-Agent paradigm named (Holonic MultiAgent Systems: HMAS). The approach of modeling used is organizational and it uses four basic concepts: Capacity, Role, Interaction and Organization (CRIO). The Traditional modeling techniques fail to capture interactions between loosely coupled aspects of a complex system. However, the organizational model of the ACO has highlighted the different roles that can occur in such optimization device. The solving approach highlights two fundamental concepts from behavioral intensification and diversification. Since, it is difficult to distinguish an intensification from a diversification behavior, though these two trends are identifiable in the organizational model of the proposed ACO, a single role can combine the roles Intensify and Diversify. So, a Manager role is identified and is responsible for the coordination of research by the colonies, and the management of the pheromone memory.

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