Assessment of a Distributed Multicriteria Decision Approach through a traffic problem

The majority of approaches for finding best compromise solutions to multicriteria optimization problems (MOP) make use of the Pareto optimality concept. However, in modeling real world problems, we often encounter MOP with large Pareto optimal alternatives to choose from. In this paper we present a multi-agent approach for solving problems in this setting. This approach is based on two main concepts, a-efficiency and plurality voting. The concept of a-efficiency allows setting up a preference ordering amongst various Pareto optimal (PO) alternatives. Whereas plurality voting procedure is used to rank the solutions set, whenever the user still has to process a large number of PO alternatives. The effectiveness of the approach is discussed, firstly, on randomly generated examples. Next, it is assessed through a practical setting related to the regulation of urban transportation networks