Applying the Assignment Model to Optimize Vehicle Allocation in a Logistics Company in Port Harcourt

The effective allocation of delivery vehicles to distribution routes is a fundamental operational challenge for logistics companies operating in Nigeria's oil-rich South South cities. This study applies the assignment model to optimize the daily allocation of vehicles to routes for a logistics firm operating in Port Harcourt, Rivers State. The company operates a fleet of 12 delivery vehicles serving 12 designated delivery zones across the Port Harcourt metropolis. A cost matrix is constructed based on historical fuel consumption, vehicle-route suitability ratings, estimated delivery time, and driver familiarity with each zone. The Hungarian algorithm is applied to derive the optimal one-to-one vehicle-to-route assignment that minimizes total operational cost. The optimal solution is compared with the company's current practice of supervisor-assigned allocation based on subjective judgment. Results indicate that the model-derived assignment reduces total daily operational cost by approximately 27 percent, primarily through better matching of fuel-efficient vehicles to longer routes and experienced drivers to high-complexity zones. The study also explores the impact of vehicle unavailability through sensitivity analysis, demonstrating that the model can quickly generate revised assignments when fleet size is reduced by one or two vehicles. Recommendations include developing a simple assignment tool within the company's dispatch software and conducting monthly model updates. This research illustrates the operational benefits of applying quantitative optimization to vehicle fleet management in urban Nigerian logistics. Keywords: assignment model, vehicle allocation, logistics, Port Harcourt, Hungarian algorithm