Real-world optimization problems typically involve multiple objectives to be optimized
simultaneously under multiple constraints and with respect to several variables. While multi …

Interactive multiobjective optimization (IMO) aims at finding the most preferred solution of a
decision maker with the guidance of his/her preferences which are provided progressively …

Abstract Multiple Criteria Decision Aiding (MCDA) offers a diversity of approaches designed
for providing the decision maker (DM) with a recommendation concerning a set of …

This article presents a review and a classification of interactive optimization methods. These
interactive methods are used for solving optimization problems. The interaction with an end …

Interactive methods are useful decision-making tools for multiobjective optimization
problems, because they allow a decision-maker to provide her/his preference information …

The growing impact of the “analytics” perspective in recent years, which integrates advanced
data-mining and learning methods, is often associated with increasing access to large …

Within disaggregation–aggregation approach, ordinal regression aims at inducing
parameters of a preference model, for example, parameters of a value function, which …

In interactive multiobjective optimization methods, the preferences of a decision maker are
incorporated in a solution process to find solutions of interest for problems with multiple …

We introduce a family of interactive evolutionary algorithms for Multiple Objective
Optimization (MOO). In the phase of preference elicitation, a Decision Maker (DM) is asked …

There is a growing demand for public participation in environmental decision-making.
However, it is unclear how a large number of citizens can best engage in such complex …