Multi-Agent Based Modeling Using Multi-Criteria Decision Analysis and OLAP System for Decision Support Problems

This paper discusses the intake of combining multi-criteria
decision analysis (MCDA) with OLAP systems, to generate
an integrated analysis process dealing with complex multi-criteria
decision-making situations. In this context, a multi-agent modeling is
presented for decision support systems by combining multi-criteria
decision analysis (MCDA) with OLAP systems. The proposed
modeling which consists in performing the multi-agent system
(MAS) architecture, procedure and protocol of the negotiation model
is elaborated as a decision support tool for complex decision-making
environments. Our objective is to take advantage from the multi-agent
system which distributes resources and computational
capabilities across interconnected agents, and provide a problem
modeling in terms of autonomous interacting component-agents.
Thus, the identification and evaluation of criteria as well as the
evaluation and ranking of alternatives in a decision support situation
will be performed by organizing tasks and user preferences between
different agents in order to reach the right decision. At the end, an
illustrative example is conducted to demonstrate the function and
effectiveness of our MAS modeling.

Authors:

• Omar Boutkhoum
• Mohamed Hanine
• Tarik Agouti
• Abdessadek Tikniouine

Keywords:

• Multidimensional Analysis
• OLAP Analysis
• Multi-criteria Decision Analysis
• Multi-Agent System
• Decision Support System.

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