Optimization of Resource and Budget Allocation for Traffic Congestion Mitigation in West, East, and South Jakarta Using A Linear Programming Approach

Abstract

Traffic congestion in DKI Jakarta has reached a critical level, with an average congestion index of 59.8% in 2025, ranking Jakarta as the 24th most congested city in the world. The structural disparity between motor vehicle growth (9–12% per year) and road network growth (only 0.01% per year) is a major contributor to this problem, resulting in estimated economic losses of IDR 45–100 trillion annually. This study optimizes resource and budget allocation for traffic congestion mitigation across 15 major road segments in West, East, and South Jakarta using a Mixed-Integer Linear Programming (MILP) approach. The objective function minimizes total daily traffic delay through three types of interventions: road widening, U-turn closures, and the deployment of additional traffic control personnel, subject to a maximum budget constraint of IDR 5 trillion, physical constraints for each road segment, a maximum availability of 1,500 personnel, and integer constraints. The model is solved using the Simplex method in Microsoft Excel Solver. The optimization results indicate that the optimal combination of interventions requires a budget of IDR 1.045 trillion and achieves a delay reduction of 625.3 minutes, leaving 84.7 minutes of delay compared with the initial 710 minutes, while covering all 15 road segments. West Jakarta accounts for the largest proportion of physical road widening (50.9%), whereas East and South Jakarta rely more heavily on non-structural interventions with higher cost–benefit ratios. The sensitivity analysis identifies a budget saturation point of IDR 1.045 trillion, beyond which additional expenditure does not yield further improvements under the specified model constraints. This study recommends the dynamic application of the optimization model and the reallocation of the remaining budget to improve public transportation.