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<p>Recently, Babaie-Kafaki et al. (AsiaPacific J Operat Res 29:1–25, 2012, Appl Soft Comput 46:220–229, 2016) have suggested a model for the fuzzy bus terminal location problem. Here, we propose a new optimization model by improving Babaie-Kafaki et al.’s model. In our model, we define new structures of neighborhoods. Also, we assume that the number of passengers corresponds to the fuzzy nodes. Using modified Kerre’s inequality, we propose a new variable neighborhood search algorithm for solving a fuzzy bus terminal location problem. In our algorithm, we consider new types of neighborhoods to have a more realistic fuzzy model. The algorithm is tested on a variety of random generated large-scale fuzzy bus terminal location problems with fuzzy coefficients. In contrast of most existing method our proposed algorithm is solved fuzzy bus terminal location problem directly. The parameters of our proposed algorithm are set by irace package to ensure fair space. To demonstrate the performance of our method, we make a comparison between our method and other existing algorithms. We make use of the non-parametric statistical test due to Wilcoxon’s test and the Dolan–Moré performance profiles to assess the performance of the numerical algorithms.</p>

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A new model for facility bus terminal location problem based on modified Kerre’s inequality

  • 期刊论文

  • 发表日期：

    2025年3月1日

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  • Sahar Rahdar,
  • Reza Ghanbari,
  • Khatere Ghorbani-Moghadam,
  • Sedigheh Sadeghi,
  • Donya Heidari

摘要

Recently, Babaie-Kafaki et al. (AsiaPacific J Operat Res 29:1–25, 2012, Appl Soft Comput 46:220–229, 2016) have suggested a model for the fuzzy bus terminal location problem. Here, we propose a new optimization model by improving Babaie-Kafaki et al.’s model. In our model, we define new structures of neighborhoods. Also, we assume that the number of passengers corresponds to the fuzzy nodes. Using modified Kerre’s inequality, we propose a new variable neighborhood search algorithm for solving a fuzzy bus terminal location problem. In our algorithm, we consider new types of neighborhoods to have a more realistic fuzzy model. The algorithm is tested on a variety of random generated large-scale fuzzy bus terminal location problems with fuzzy coefficients. In contrast of most existing method our proposed algorithm is solved fuzzy bus terminal location problem directly. The parameters of our proposed algorithm are set by irace package to ensure fair space. To demonstrate the performance of our method, we make a comparison between our method and other existing algorithms. We make use of the non-parametric statistical test due to Wilcoxon’s test and the Dolan–Moré performance profiles to assess the performance of the numerical algorithms.