Variable Range-based Interaction Preference Multi-objective Optimization Algorithm through Objective Decomposition

This paper proposes a variable range-based interaction preference multi-objective optimization algorithm through objective decomposition (VR-MOEA-OD). VR-MOEA-OD focuses on finding the preferred solutions of decision maker (DM) and can adjust the size of the preference range based on the DM’s needs. First, the DM is asked to provide a preference direction and the number of needed solutions. Then, the algorithm searches for the DM’s preferred solutions using the multi-objective evolutionary algorithm based on objective decomposition (MOEA-OD). If unsatisfied with the results, the DM needs to provide a range parameter to adjust the size of preference range and respecify the number of desired solutions. Based on the range parameter and the change in the number of solutions required before and after the interaction, VR-MOEA-OD can modulate the size of the preference range, either enlarging or narrowing the preference range. The results indicate that VR-MOEA-OD can fully utilize preference information and satisfy the interaction information provided by the DM to achieve desired results.