What Lies beyond the Pareto Front? A Survey on Decision-Support Methods for Multi-Objective Optimization
Published in International Joint Conference on Artificial Intelligence, Macau 2023, 2023
Recommended citation: Osika, Z., Zatarain Salazar, J., Roijers, D. M., Oliehoek, F. A., & Murukannaiah, P. K. (2023). What Lies beyond the Pareto Front? A Survey on Decision-Support Methods for Multi-Objective Optimization. In E. Elkind (Ed.), Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI-23 (pp. 6741–6749). International Joint Conferences on Artificial Intelligence Organization.
We present a review that unifes decision-support methods for exploring the solutions produced by multi-objective optimization (MOO) algorithms. As MOO is applied to solve diverse problems, approaches for analyzing the trade-offs offered by MOO algorithms are scattered across felds. We provide an overview of the advances on this topic, including methods for visualization, mining the solution set, and uncertainty exploration as well as emerging research directions, including interactivity, explainability, and ethics. We synthesize these methods drawing from different felds of research to build a unifed approach, independent of the application. Our goals are to reduce the entry barrier for researchers and practitioners on using MOO algorithms and to provide novel research directions.