moGrams: a network-based methodology for visualizing the set of non-dominated solutions in multiobjective optimization

TL;DR

moGrams is a network-based visualization method that jointly displays non-dominated solutions in both objective and design spaces, aiding decision makers in understanding complex multiobjective problems.

Contribution

It introduces a novel network methodology for visualizing relationships among solutions in multiobjective optimization, integrating design and objective spaces in a single view.

Findings

Effective visualization of solution relationships in multiobjective problems.

Versatile application to various multi-criteria problems.

Enhanced decision-making support through interactive network modifications.

Abstract

An appropriate visualization of multiobjective non-dominated solutions is a valuable asset for decision making. Although there are methods for visualizing the solutions in the design space, they do not provide any information about their relationship. In this work, we propose a novel methodology that allows the visualization of the non-dominated solutions in the design space and their relationships by means of a network. The nodes represent the solutions in the objective space, while the edges show the relationships between the solutions in the design space. Our proposal (called moGrams) thus provides a joint visualization of both objective and design spaces. It aims at helping the decision maker to get more understanding of the problem so that (s)he can choose the more appropriate final solution. moGrams can be applied to any multicriteria problem in which the solutions are related by a similarity metric. Besides, the decision maker interaction is facilitated by modifying the network based on the current preferences to obtain a clearer view. An exhaustive experimental study is performed using three multiobjective problems in order to show both the usefulness and versatility of moGrams. The results exhibit interesting characteristics of our methodology for visualizing and analyzing solutions of multiobjective problems.