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<p>This study investigates a specific category of Marine Inventory Routing Problems (MIRPs), which involves the supply and demand management of a port inventory under vessel routing constraints. MIRP is typically formulated as mixed-integer linear programming models which present computational challenges when employing existing solvers. To address the computational difficulties of the MIRP, researchers have explored numerous approximation, decomposition, and heuristic approaches to generate effective and practical solutions. Given that the feasibility pump method (FPM) can find feasible solutions for MILP models, this paper seeks to adopt a recently addressed version of FPM to find feasible solutions for MIRP. We refer to our approach as a heuristic method based on fractional programming (HBFP) and, through computational experiments, show its superiority over the FPM when tackling large-scale instances of MIRP.</p>

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Fractional Programming-Based Heuristic: An Efficient Method for Marine Inventory Routing Problem

  • 期刊论文

  • 发表日期：

    2025年6月4日

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  • Mohammad Nasir Yarahmadi,
  • Seyed Ali MirHassani,
  • Farnaz Hooshmand

摘要

This study investigates a specific category of Marine Inventory Routing Problems (MIRPs), which involves the supply and demand management of a port inventory under vessel routing constraints. MIRP is typically formulated as mixed-integer linear programming models which present computational challenges when employing existing solvers. To address the computational difficulties of the MIRP, researchers have explored numerous approximation, decomposition, and heuristic approaches to generate effective and practical solutions. Given that the feasibility pump method (FPM) can find feasible solutions for MILP models, this paper seeks to adopt a recently addressed version of FPM to find feasible solutions for MIRP. We refer to our approach as a heuristic method based on fractional programming (HBFP) and, through computational experiments, show its superiority over the FPM when tackling large-scale instances of MIRP.