Artículo
InDM2: Interactive Dynamic Multi-Objective Decision Making Using Evolutionary Algorithms
Autor/es | Nebro, Antonio J.
Ruiz, Ana B. Barba González, Cristóbal García Nieto, José Manuel Luque, Mariano Aldana Montes, José F. |
Departamento | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial |
Fecha de publicación | 2018 |
Fecha de depósito | 2021-05-07 |
Publicado en |
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Resumen | Dynamic optimization problems involving two or more conflicting objectives appear in many real-world scenarios,
and more cases are expected to appear in the near future with the increasing interest in the analysis ... Dynamic optimization problems involving two or more conflicting objectives appear in many real-world scenarios, and more cases are expected to appear in the near future with the increasing interest in the analysis of streaming data sources in the context of Big Data applications. However, approaches combining dynamic multiobjective optimization with preference articulation are still scarce. In this paper, we propose a new dynamic multi-objective optimization algorithm called InDM2 that allows the preferences of the decision maker (DM) to be incorporated into the search process. When solving a dynamic multi-objective optimization problem with InDM2, the DM can not only express her/his preferences by means of one or more reference points (which define the desired region of interest), but these points can be also modified interactively. InDM2 is enhanced with methods to graphically display the different approximations of the region of interest obtained during the optimization process. In this way, the DM is able to inspect and change, in optimization time, the desired region of interest according to the information displayed. We describe the main features of InDM2 and detail how it is implemented. Its performance is illustrated using both synthetic and real-world dynamic multi-objective optimization problems. |
Agencias financiadoras | Ministerio de Ciencia e Innovación (MICIN). España Junta de Andalucía |
Identificador del proyecto | TIN2017-86049-R
TIN2014- 58304 ECO2014-56397-P P11-TIC-7529 P12-TIC-1519 |
Cita | Nebro, A.J., Ruiz, A.B., Barba González, C., García Nieto, J.M., Luque, M. y Aldana Montes, J.F. (2018). InDM2: Interactive Dynamic Multi-Objective Decision Making Using Evolutionary Algorithms. Swarm and Evolutionary Computation, 40 (June 2018), 184-195. |