Multiobjective Evolutionary Computation for Market Segmentation

Ying Liu

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Paper

Multiobjective Evolutionary Computation for Market Segmentation

Topics: Applications: Games and Entertainment Technologies, Evolutionary Robotics, Evolutionary Art and Design, Industrial and Real World applications, Computational Economics and Finance; Evolutionary Multi-objective Optimization; Evolutionary Search and Meta-heuristics

In Proceedings of the 13th International Joint Conference on Computational Intelligence - Volume 0IJCCI, 149-154, 2021

Author: Ying Liu

Affiliation: College of Business, California State University Long Beach, Long Beach, CA, U.S.A.

Keyword(s): Market Segmentation, Multiobjective Evolutionary Computation, Pareto Optimal.

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.

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Paper citation in several formats:

Liu, Y. (2021). Multiobjective Evolutionary Computation for Market Segmentation. In Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - IJCCI; ISBN 978-989-758-534-0; ISSN 2184-3236, SciTePress, pages 149-154. DOI: 10.5220/0010684400003063

@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) - IJCCI},
year={2021},
pages={149-154},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010684400003063},
isbn={978-989-758-534-0},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - IJCCI
TI - Multiobjective Evolutionary Computation for Market Segmentation
SN - 978-989-758-534-0
IS - 2184-3236
AU - Liu, Y.
PY - 2021
SP - 149
EP - 154
DO - 10.5220/0010684400003063
PB - SciTePress