@inproceedings {pub3918,
	title = {Identifying Solutions of Interest for Practical Many-objective Problems using Recursive Expected Marginal Utility},
	author = {Hemant Kumar Singh AND Tapabrata Ray AND Tobias Rodemann AND Markus Olhofer},
	year = {2019},
	month = {July},
	abstract = {Real-world design problems often involve optimization of multiple conflicting criteria, referred to as multi-objective optimization problems. In the recent years, increasing attention has been paid to make the multi-objective evolutionary algorithms scalable to problems with more than 3 objectives, also colloquially termed many-objective optimization problems. This has led to the emergence of a number of new techniques that can deliver a set of trade-off solutions to approximate the Pareto optimal front of the problem. However, subsequent selection of solution(s) from this large trade-off set for final implementation/decision making has received scarce attention in the current literature. The aim of this paper is to study and demonstrate the performance of recursive expected marginal utility (EMU^r ) approach for informed decision-making. Towards this goal, we apply the EMU^r approach to identify solutions of interest for two practical examples and analyze the obtained set of solutions. The study highlights the desirable trade-off characteristics that the chosen solutions have over the rest of the trade-off set, highlighting its potential as a decision-making tool, especially the cases where other preference information or domain knowledge is unavailable.

},
	publisher = {ACM},
	booktitle = {GECCO Workshop on Real-world Applications of  Continuous and Mixed-integer Optimization },
	city = {Prague}
}