Prioritization of Road Rehabilitation Investments in Post-Conflict South Sudan Using Multi-Criteria Decision Analysis

South Sudan's post-conflict road rehabilitation agenda faces a fundamental challenge: a backlog of deteriorated road infrastructure vastly exceeding available funding, with no transparent or technically defensible framework for directing limited resources where they will generate the greatest national benefit. This paper presents a rigorous Multi-Criteria Decision Analysis (MCDA) framework integrating the Analytic Hierarchy Process (AHP) for criteria weighting and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for alternative ranking, applied to the prioritization of road rehabilitation investments across twelve candidate road segments in South Sudan. Seven evaluation criteria are identified and operationalized — pavement condition index, traffic volume, conflict exposure index, economic impact coefficient, population served, climate vulnerability score, and network connectivity index — and their relative weights are determined through a structured expert elicitation survey involving 34 civil engineering and transport planning experts. A decision matrix encompassing quantitative field data, remote-sensing indicators, and socio-economic survey outputs is constructed and processed through the TOPSIS algorithm to generate a closeness coefficient ranking. Results identify the Juba–Bor segment of National Highway N-8 (C_i = 0.831) as the highest-priority rehabilitation investment, followed by the Malakal–Renk Corridor (C_i = 0.794) and the Wau–Aweil Road (C_i = 0.762). A budget-constrained optimisation model using integer linear programming selects an optimal rehabilitation portfolio of six segments within a USD 75 million capital budget, yielding a combined TOPSIS benefit score of 4.411. Sensitivity analysis confirms the stability of the top-fou