We describe an interactive evolutionary algorithm to solve multiobjective optimization problems. It is based on a preference-based evolutionary multiobjective optimization algorithm called WASF-GA. In the interactive version of WASF-GA to be introduced, at each iteration, the decision maker can provide desirable aspiration values and several nondominated objective vectors are generated based on them. They are filtered and shown to the decision maker.
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