Minimizing Fuel Consumption in Cross-State Truck Routing for a Logistics Firm Operating in North East Nigeria

Long-distance freight transportation in Nigeria's North East geopolitical zone is constrained by poor road conditions, security challenges, and fuel price volatility, making route optimization a commercially and socially significant problem. This study applies shortest path algorithms, specifically Dijkstra's algorithm, and the vehicle routing problem framework to minimize fuel consumption for a logistics firm operating a fleet of six heavy-duty trucks across Gombe, Yobe, and Bauchi States. A weighted road network graph is constructed from field surveys and state road maps, with edge weights representing fuel consumption estimates adjusted for road quality indices obtained from the Federal Ministry of Works. Weekly freight demand data covering 24 destinations are obtained from the company's dispatch records. Dijkstra's algorithm identifies minimum fuel-cost paths between depot and each destination, and these paths are incorporated into a VRP formulation solved using a greedy nearest neighbour heuristic. The optimized routing plan is benchmarked against the current driver-determined routing practice. Results show that the optimized plan reduces total weekly fuel consumption by an estimated 18 percent, equivalent to approximately N280,000 in monthly savings at current fuel prices. Road quality emerges as a more significant driver of fuel cost than distance on six of the 24 routes. Recommendations include integrating route optimization software into the company's dispatch operations and advocating for targeted road rehabilitation on high-frequency corridors. Keywords: fuel minimization, vehicle routing, Dijkstra's algorithm, North East Nigeria, logistics