Network Flow Optimization for Oil Pipeline Distribution in Bayelsa State

The distribution of crude oil and refined petroleum products through pipeline networks in Nigeria's oil-producing region involves complex logistical challenges exacerbated by infrastructure aging, illegal bunkering, and demand variability. This study applies network flow optimization techniques, specifically the maximum flow and minimum cost flow algorithms, to evaluate the efficiency of a petroleum pipeline network operated in Bayelsa State, South South Nigeria. Network topology data, including pipeline capacities, node demands, and operational cost parameters, were obtained from a pipeline operating company through official data request. The maximum flow algorithm is used to determine the theoretical throughput capacity of the network, while the minimum cost flow model identifies the routing plan that satisfies all delivery demands at minimum total pumping and transportation cost. Results reveal that the existing routing plan operates at only 74 percent of maximum network capacity due to sub-optimal flow allocation across parallel routes. The minimum cost flow solution achieves the same total delivery volume at 17 percent lower operational cost by rerouting flows through underutilized pipeline segments. The study also identifies three network nodes where capacity upgrades would yield the greatest throughput improvements. Recommendations include adopting minimum cost flow optimization as part of the company's operational planning cycle and prioritizing maintenance at high-utilization pipeline segments. This research demonstrates the applicability of network flow models to petroleum logistics in Nigeria's oil-producing zone. Keywords: network flow optimization, pipeline distribution, petroleum logistics, Bayelsa State, minimum cost flow