Interactive methods of multiobjective optimization repetitively derivePareto optimal solutions based on decision maker’s preference information and presentthe obtained solutions for his/her consideration. Some interactive methods save theobtained solutions into a solution pool and, at each iteration, allow the decisionmaker considering any of solutions obtained earlier. This feature contributes to theflexibility of exploring the Pareto optimal set and learning about the optimizationproblem. However, in the case of many objective functions, the accumulation ofderived solutions makes accessing the solution pool cognitively difficult for the decisionmaker. We propose to enhance interactive methods with visualization of the setof solution outcomes using dimensionality reduction and interactive mechanisms forexploration of the solution pool. We describe a proposed visualization technique anddemonstrate its usage with an example problem solved using the interactive methodNIMBUS.
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