Preference Incorporation into Evolutionary Multiobjective Optimization using Preference Information Implicit in a Set of Assignment Examples

DOI

10.2991/.2013.22How to use a DOI?

Keywords

evolutionary algorithms; multiobjective op-timization; preference incorporation; multicriteria sorting

Abstract

Nowadays, most approaches in the evolutionary multiobjective optimization literature concentrate mainly on adapting an evolutionary algorithm to generate an ap-proximation of the Pareto frontier. However, this does not solve the problem. We present a new idea to incorporate into a MOEA the Decision Maker (DM) preferences, ex-pressed in a set of solutions assigned to ordered catego-ries. We modified the Non-dominated Sorting Genetic Algorithm 2 (NSGA2) to make selective pressure towards non-dominated solutions that belong to the most preferred category. In several instances, on the project portfolio problem, our proposal outperforms the standard NSGA2, achieving non-dominated solutions that best match the DM’s preferences.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Laura Cruz-Reyes
AU  - Eduardo Fernandez
AU  - Rafael Olmedo
AU  - Patricia Sanchez
AU  - Jorge Navarro
PY  - 2013/10
DA  - 2013/10
TI  - Preference Incorporation into Evolutionary Multiobjective Optimization using Preference Information Implicit in a Set of Assignment Examples
BT  - Proceedings of the Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support
PB  - Atlantis Press
SP  - 179
EP  - 187
SN  - 1951-6851
UR  - https://doi.org/10.2991/.2013.22
DO  - 10.2991/.2013.22
ID  - Cruz-Reyes2013/10
ER  -