A Novel Multi-Objective Optimisation Framework for Sustainable Urban Road Network Design in Nigerian Cities

Urban road network design in Nigerian cities must simultaneously balance multiple competing objectives including mobility efficiency, construction cost, environmental impact, community disruption, and long-term maintenance cost, yet existing planning practice employs single-objective or weighted-sum approaches that inadequately represent the true Pareto frontier of design options. This study develops a novel multi-objective optimisation framework for sustainable urban road network design in Nigerian cities. A graph-theoretic road network representation is coupled with a multi-objective evolutionary algorithm (NSGA-III) to generate Pareto-optimal network design solutions across five objectives: travel time efficiency, life cycle cost, CO2 emissions, noise exposure index, and pedestrian accessibility. Objective functions are calibrated using Nigerian construction, maintenance, and traffic emission data. The framework is applied to the design of a 45-node test network representing a developing urban district in Abuja and to the expansion planning of existing networks in Enugu and Kano. Scenario analysis evaluates robustness of Pareto solutions under three future demand scenarios. Results demonstrate that the multi-objective approach identifies design solutions achieving 18 to 34 percent better multi-criteria performance than single-objective least-cost designs. The Pareto frontier reveals significant trade-offs between pedestrian accessibility and vehicle efficiency that are invisible in single-objective frameworks. The study provides an original methodological contribution to sustainable transport infrastructure planning applicable across Nigerian urban planning contexts.

Keywords: multi-objective optimisation, urban road network, NSGA-III, sustainable transport, Nigerian cities