A classification scheme for agent based approaches to dynamic optimization

Abstract

Several papers in the literature employ agent-based modeling approach for providing reasonable solutions to dynamic optimization problems (DOPs). However, these studies employ a variety of agent-based modeling approaches with different strategies and features for different DOPs. On the other hand, there is an absence in the literature of a formal representation of the existing agent-based solution strategies. This paper proposes a representation scheme indicating how the solution strategies with agent-based approach can be summarized in a concise manner. We present these in a tabular form called "Agent Based Dynamic Optimization Problem Solution Strategy" (ABDOPSS). ABDOPSS distinguishes different classes of agent based algorithms (via communication type, cooperation type, dynamism domain and etc.) by specifying the fundamental ingredients of each of these approaches with respect to problem domain (problems with dynamic objective functions, constraints and etc.). This paper also analyzes 18 generic studies in the literature employing agent-based modeling based on ABDOPSS.