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  • 标题:A bibliometric analysis of the product line design problem
  • 本地全文:下载
  • 作者:Alma Montserrat Romero-Serrano ; Omar Ahumada-Valenzuela ; Juan Carlos Leyva-Lopez
  • 期刊名称:Inquietud Empresarial
  • 印刷版ISSN:0121-1048
  • 电子版ISSN:2422-3220
  • 出版年度:2021
  • 卷号:21
  • 期号:1
  • 页码:11-33
  • 出版社:Universidad Pedagógica y Tecnológica de Colombia
  • 摘要:In the product design problem, firms aim to find suitable configurations of product attributes with the objective of increasing their participation in the marketplace. This problem belongs to the field of quantitative marketing and is considered a NP-Hard problem, due to its wide search space for an optimal solution. Among the related literature, there are different methodologies to address this problem, gaining ground those that apply metaheuristics, with an emphasis in Genetic Algorithms. The main aim of this work is to present an overview of the most significant contributions in this area using a bibliometric analysis approach. The paper uses Scopus database and Web of Science Core Collection, in order to obtain leading and the most influential articles, conferences papers, journals, authors, institutions and countries. The results highlight Kwong, C.K. as the most productive author while Nagamachi M. is the most influential author. Furthermore, China is the leading country in this research field. The use of Genetic Algorithms in the solutions of the Product Design Problem is a growing area of study with important development of methodologies and approaches.
  • 其他摘要:In the product design problem, firms aim to find suitable configurations of product attributes with the objective of increasing their participation in the marketplace. This problem belongs to the field of quantitative marketing and is considered a NP-Hard problem, due to its wide search space for an optimal solution. Among the related literature, there are different methodologies to address this problem, gaining ground those that apply metaheuristics, with an emphasis in Genetic Algorithms. The main aim of this work is to present an overview of the most significant contributions in this area using a bibliometric analysis approach. The paper uses Scopus database and Web of Science Core Collection, in order to obtain leading and the most influential articles, conferences papers, journals, authors, institutions and countries. The results highlight Kwong, C.K. as the most productive author while Nagamachi M. is the most influential author. Furthermore, China is the leading country in this research field. The use of Genetic Algorithms in the solutions of the Product Design Problem is a growing area of study with important development of methodologies and approaches. JEL Codes: C00, C02 Received: 07/10/2020. Accepted: 20/02/2021. Published: 01/06/2021.
  • 关键词:bibliométrico; problema de diseño de línea de producto; algoritmos genéticos.;Bibliometrico;problema de diseño de línea de producto;desarrollo de línea de prodcuto;nueva línea de producto;diseño de línea de producto;algoritmo genetico
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