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Investigating Nigerian Product Distribution Model: Advanced Mathematical Optimization and Multi-Objective Mesh Routing for Food Distribution Logistics in Post-Subsidy Nigeria

Author

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  • Gokir Justine Ali

    (Department of Computer Science, Federal University of Education, Pankshin Plateau State, Nigeria)

  • Dandam Nannim Dandam

    (Department of Computer Science, Federal University of Education, Pankshin Plateau State, Nigeria)

  • Paul Palangnen

    (Department of Computer Science, Federal University of Education, Pankshin Plateau State, Nigeria)

  • Yakubu Bilshak Gonchor

    (Department of Computer Science, Federal University of Education, Pankshin Plateau State, Nigeria)

  • Kilson Panshak Bitrus

    (Directorate of Academic Planning, Federal University of Education, Pankshin, Plateau State, Nigeria)

Abstract

The removal of fuel subsidies in Nigeria in 2023 resulted in a 150–200% increase in transportation costs, severely disrupting food distribution systems in a country where logistics costs account for approximately 22% of GDP. This study develops and evaluates a dual-optimization framework for minimizing food distribution costs under volatile economic conditions. First, classical transportation methods—Northwest Corner Method (NWCM), Least Cost Method (LCM), Vogel’s Approximation Method (VAM), and Modified Distribution (MODI)—are evaluated using a 4×5 supply-demand case study (50,000 metric tons). Second, a novel Gokir-Nannim (GN) Model incorporating adaptive penalty functions is developed and integrated with Multi-Objective Mesh Routing (MOMR). Results indicate that VAM achieves a 37.4% cost reduction compared to NWCM, while the GN Model achieves 39.6%. Integration with MOMR produces a 41% reduction in Total Transportation Overhead (TTO), while simultaneously reducing delivery time by 28% and increasing reliability by 17%. Sensitivity analysis under ±30% fuel volatility confirms superior resilience of GN+MOMR compared to classical methods. The findings demonstrate that adaptive, multi-objective optimization can substantially mitigate the inflationary effects of subsidy removal and reduce national logistics costs from 22% to approximately 13% of GDP.

Suggested Citation

  • Gokir Justine Ali & Dandam Nannim Dandam & Paul Palangnen & Yakubu Bilshak Gonchor & Kilson Panshak Bitrus, 2026. "Investigating Nigerian Product Distribution Model: Advanced Mathematical Optimization and Multi-Objective Mesh Routing for Food Distribution Logistics in Post-Subsidy Nigeria," International Journal of Latest Technology in Engineering, Management & Applied Science, RSIS International, vol. 15(3), pages 755-766, March.
  • Handle: RePEc:bjf:ijltem:v:15:y:2026:i:3:a:2224
    DOI: 10.51583/IJLTEMAS.2026.150300062
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