Multiobjective Evolutionary Computation for Market Segmentation

Ying Liu

2021

Abstract

The market segmentation, by its computational essence, is a NP-hard multicriteria problem. Multiobjective evolutionary algorithms are developed to optimize multiple objectives simultaneously and can generate a set of Pareto optimal solutions. As a proven meta-heuristic technique, multiobjective evolutionary computation is robust in handling different data types, various business constraints and different objective function forms. The generated Pareto optimal solution set gives a holistic view of possible solutions that bring business insights and allow big flexibility in solution selection. These features make the multiobjective evolution computation a good fit for market segmentation problems. There are challenges in every phase in implementation of multiobjective evolutionary computation for market segmentation.

Paper Citation

in Harvard Style

Liu Y. (2021). Multiobjective Evolutionary Computation for Market Segmentation. In Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - Volume 1: IJCCI; ISBN 978-989-758-534-0, SciTePress, pages 149-154. DOI: 10.5220/0010684400003063

in Bibtex Style

@conference{ijcci21,
author={Ying Liu},
title={Multiobjective Evolutionary Computation for Market Segmentation},
booktitle={Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - Volume 1: IJCCI},
year={2021},
pages={149-154},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010684400003063},
isbn={978-989-758-534-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - Volume 1: IJCCI
TI - Multiobjective Evolutionary Computation for Market Segmentation
SN - 978-989-758-534-0
AU - Liu Y.
PY - 2021
SP - 149
EP - 154
DO - 10.5220/0010684400003063
PB - SciTePress