MILP for Multimodal Urban Transport: Formal and Informal Sectors

This study presents a mixed-integer linear programming (MILP) formulation for optimizing multimodal urban transportation networks that integrate formal and informal public transport sectors. Whereas prior optimization approaches have predominantly addressed regulated formal services, the proposed model explicitly incorporates informal operators prevalent in many African cities. The objective is to minimize total user travel time, comprising in-vehicle time, waiting time at stops, and trans-fer time between modes, subject to flow conservation constraints, limits on mode changes, and sector-specific operational rules. Under the assumption of static demand and known arc travel times, computational experiments use realistic synthetic instances calibrated to reflect operating characteristics of the operators providing public transport services in Abidjan, Côte d’Ivoire—informed by close observation of non-public operational patterns and published mobility statistics—with 5 to 24 logical stops and up to 2,487 active arcs. Compared with formal-only system con-figurations, the integrated formal–informal formulation reduces total travel time by up to 53% on the largest tested instances (24 stops; with smaller gains on smaller networks). All instances were solved with IBM CPLEX 22.11; maximum solve times were 1.63 s on corridor instances (n = 24) and 0.69 s on an extended set with n = 100 (Intel Core i7, 16 GB RAM). These findings indicate that coordinated planning of formal and informal transport can materially improve urban mobility in developing cities.