Work

Icons for Software Implementations of Interactive Multiobjective Optimization Methods: A Semantic Distance Study

Year: 2025

Type: article

Abstract: ABSTRACT Multiobjective optimization problems involve several conflicting objective functions to be optimised simultaneously and solutions to these problems represent different trade‐offs. When applying interactive methods, a decision maker with domain expertise provides one's preference information over several iterations, according to which new solutions are computed until finding a solution with the most preferred trade‐offs. Publications on interactive multiobjective optimization methods mainly focus on the optimisation algorithm, and little attention is paid to their implementations, not to mention the development of user interfaces that enable interaction with the decision maker. User interfaces involve icons but there are no studies about icons for the specific functionalities of multiobjective optimization methods. Icons convey meaning effectively to users interacting with technology. With these small pictorial representations, information on system functionalities is communicated quickly. However, the immediacy of icon recognition can also lead to misunderstandings and difficulties in using the system if they are not designed properly. Semantic distance in icon design indicates the closeness of the pictorial representation to its intended functionality and, thus, functions as the main principle in designing effective icons. An empirical study () was conducted to examine the semantic distances of icons for interactive multiobjective optimization methods implemented in an open‐source software framework. The study addressed the main functionalities. According to our main findings, we suggest an icon set for the considered functionalities, to enable fluent interaction with decision makers and other involved parties utilising interactive multiobjective optimization methods via user interfaces.

Source: Journal of Multi-Criteria Decision Analysis

DOI: 10.1002/mcda.70010

Authors: Johanna Silvennoinen, Giomara Lárraga Maldonado, Ana B. Ruiz, Francisco Ruiz, Giovanni Misitano, Kaisa Miettinen

Institutions: University of Jyväskylä, Universidad de Málaga

Language: English

Topic: Advanced Multi-Objective Optimization Algorithms

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,900

Funder: Academy of Finland