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<p>The city gate station (CGS) location selection problem refers to selecting physical points before entering the cities in the natural gas pipeline system for installing CGS, which decreases the gas pressure in cities. This research addresses the problem while considering the budget and distance constraints with the fuzzy multi-criteria approach in a part of the Iranian natural gas network. In order to solve the problem, we propose a stepwise multi-criteria decision-making (MCDM) framework which contains (1) weighting the criteria by the fuzzy best–worst method, (2) evaluating and scoring the potential locations using a fuzzy TOPSIS approach, (3) formulating a fuzzy mixed integer linear program (MILP) using the obtained scores to respect the problem limitations and select the best possible set of locations, (4) performing a sensitivity analysis. The developed framework contributes to the literature by proposing an approach for agglomerating fuzzy MCDM and MILP to select the best alternative while meeting the constraints. The obtained results revealed the effectiveness of the proposed framework.</p>

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A fuzzy multi-criteria decision-making framework for constrained city gate station location selection problem in the natural gas network of Iran

  • 期刊论文

  • 发表日期：

    2025年7月28日

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  • Seyed-Hadi Mirghaderi,
  • Shima Roosta,
  • Arash Bazyar,
  • Sadegh Niroomand

摘要

The city gate station (CGS) location selection problem refers to selecting physical points before entering the cities in the natural gas pipeline system for installing CGS, which decreases the gas pressure in cities. This research addresses the problem while considering the budget and distance constraints with the fuzzy multi-criteria approach in a part of the Iranian natural gas network. In order to solve the problem, we propose a stepwise multi-criteria decision-making (MCDM) framework which contains (1) weighting the criteria by the fuzzy best–worst method, (2) evaluating and scoring the potential locations using a fuzzy TOPSIS approach, (3) formulating a fuzzy mixed integer linear program (MILP) using the obtained scores to respect the problem limitations and select the best possible set of locations, (4) performing a sensitivity analysis. The developed framework contributes to the literature by proposing an approach for agglomerating fuzzy MCDM and MILP to select the best alternative while meeting the constraints. The obtained results revealed the effectiveness of the proposed framework.