arrow
Return

Using Choquet integral as preference model in interactive evolutionary multiobjective optimization

delete2016-05-01
delete80
delete
OA
AI
J
Juergen Branke
S
Salvatore Corrente *
S
Salvatore Greco
R
Roman Słowiński
P
Piotr Zielniewicz
DOI:10.1016/j.ejor.2015.10.027delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
We propose an interactive multiobjective evolutionary algorithm that attempts to discover the most preferred part of the Pareto-optimal set. Preference information is elicited by asking the user to compare some solutions pairwise. This information is then used to curb the set of compatible user's value functions, and the multiobjective evolutionary algorithm is run to simultaneously search for all solutions that could potentially be the most preferred. Compared to previous similar approaches, we implement a much more efficient way of determining potentially preferred solutions, that is, solutions that are best for at least one value function compatible with the preference information provided by the decision maker. For the first time in the context of evolutionary computation, we apply the Choquet integral as a user's preference model, allowing us to capture interactions between objectives. As there is a trade-off between the flexibility of the value function model and the complexity of learning a faithful model of user's preferences, we propose to start the interactive process with a simple linear model but then to switch to the Choquet integral as soon as the preference information can no longer be represented using the linear model. An experimental analysis demonstrates the effectiveness of the approach. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
Keywords:
Multiobjective optimization
Evolutionary algorithms
Interaction between criteria
Choquet integral
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

European Journal of Operational Research cover
European Journal of Operational Research
IF:
6
Papers:
2.2W
Citations:
6.4W

Organization

P
Polish Academy of Sciences
Scholars:
3.0W
Papers: 3.1W
Citations: 3.1W
U
University of Catania
Scholars:
1.9W
Papers: 1.4W
Citations: 20
U
University of Warwick
Scholars:
2.2W
Papers: 2.2W
Citations: 85
researcher View more organizations
Cited Papers

Cited Papers

The EURO-GANEX Process: Current Status of Flowsheet Development and Process Safety Studies
err2016-01-01
err0
errOAAI
errRobin Taylor; Mike Carrott; Hitos Galan; Andreas Geist; Xavier Hères; Chris Maher; Chris Mason; Rikard Malmbeck; Manuel Miguirditchian; Giuseppe Modolo; Chris Rhodes; Mark Sarsfield; Andreas Wilden
errShare
errSave
Assessing non-additive utility for multicriteria decision aid
err2004-11-01
err101
PREAI
errAngilella, S; Greco, S; Lamantia, F; Matarazzo, B
errShare
errSave
Guidance in evolutionary multi-objective optimization
err2001-06-01
err242
PREAI
errBranke, J; Kaussler, T; Schmeck, H
errShare
errSave
Robust ordinal regression in preference learning and ranking
err2013-07-27
err149
errOAAI
errCorrente, Salvatore; Greco, Salvatore; Kadzinski, Milosz; Slowinski, Roman
errShare
errSave
Learning Value Functions in Interactive Evolutionary Multiobjective Optimization
err2015-02-01
err67
errOAAI
errBranke, Juergen; Greco, Salvatore; Slowinski, Roman; Zielniewicz, Piotr
errShare
errSave
researcher View more