Optimization of Bridge Placement Along

The petroleum logistics network of South Sudan spans 1,865 km of classified roads crossing more than 58 river channels, of which only 17 (29%) are currently bridged. During the annual wet season, unbridged crossings render 340–520 km of oil access road intermittently impassable, disrupting crude oil tanker operations for 15–120 days per year and imposing estimated economic losses of USD 68–140 million annually. Determining which of the remaining 41 crossings to bridge, and in what sequence, given a constrained capital budget of USD 80–120 million, constitutes a complex spatial optimisation problem requiring integration of GIS-based multi-criteria analysis, graph-theoretic network performance modelling, and economic cost-benefit analysis. This paper presents a comprehensive GIS and network analysis framework to optimise bridge placement across five petroleum logistics corridors — Juba–Malakal, Juba–Bentiu, Malakal–Renk, Bentiu–Wau, and Juba–Torit — applying three complementary optimisation methods: the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for site prioritisation, Pareto front analysis for budget-constrained portfolio selection, and betweenness centrality analysis for network-level impact quantification. Ten candidate bridge sites are evaluated against eight weighted criteria including traffic volume, flood hazard, river hydraulics, detour cost, geotechnical conditions, seismic hazard, social access equity, and environmental sensitivity. The TOPSIS-optimal sequence identifies the White Nile km 320 crossing (Route A) as the highest-priority investment, with an annual savings-to-cost ratio of USD 4.85M per USD 18.5M capital investment and a Criticality Index of 0.847. Implementation of the full five-priority portfolio generates a 31% reduc