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Multi-objective evolutionary product bundling: a case study

Tunali, Okan ; Tugrul Bayrak, Ahmet ; Sanchez-Anguix, Víctor ; Aydogan, Reyhan

ACM 2021

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Citações Citado por
  • Título:
    Multi-objective evolutionary product bundling: a case study
  • Autor: Tunali, Okan ; Tugrul Bayrak, Ahmet ; Sanchez-Anguix, Víctor ; Aydogan, Reyhan
  • Assuntos: Bundle generation ; CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL ; Decision support systems ; Evolutionary algorithms ; Genetic algorithm ; Multi-objective optimization
  • Notas: 10.5267/j.dsl.2017.4.005
    10.1016/j.ejor.2019.11.066
    10.1109/IFSA-NAFIPS.2013.6608442
    10.1016/j.cie.2016.12.045
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    10.1007/s40547-017-0075-x
    10.1016/j.compstruc.2017.03.023
    10.1007/978-0-387-85820-3_1
    GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion
    10.1145/3308558.3313568
    10.1016/j.asoc.2018.11.049
    10.1016/j.ijpe.2013.02.006
    Julio 10-14,2021
    10.1108/10610420310498795
    10.1016/j.knosys.2016.08.013
    Genetic and Evolutionary Computation Conference (GECCO 2021)
    10.1145/3077136.3080724
    Online
    https://doi.org/10.1145/3449726.3463219
    10.1007/978-3-642-41033-8_29
    10.1016/j.elerap.2006.04.006
  • Descrição: [EN] Product bundling is a strategy conducted by marketing decisionmakers to combine items or services for targeted sales in today¿s competitive business environment. Targeted sales can be in various forms, like increasing the likelihood of a purchase, promoting some products among a specific customer segment, or improving user experience. In this study, we propose an evolutionary product bundle generation strategy that is based on the NSGA-II algorithm. The proposed approach is designed as a multi-objective optimization procedure where the objectives are designed in terms of desired bundle feature distributions. The designed genetic algorithm is flexible and allows decision-makers to specify objectives such as price, season, item similarity and association with bundle size constraints. In the experiments,we showthat the evolutionary approach enables us to generate Pareto solutions compared to the initial population. Tunali, O.; Tugrul Bayrak, A.; Sanchez-Anguix, V.; Aydogan, R. (2021). Multi-objective evolutionary product bundling: a case study. ACM. 1622-1629. https://doi.org/10.1145/3449726.3463219
  • Editor: ACM
  • Data de criação/publicação: 2021
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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