A Mixed Integer Linear Programming Model for Cost and Carbon Aware LPG Vessel Speed Optimization under Terminal Congestion

Abstract

Port congestion has become one of the major operational challenges in LPG logistics because it increases vessel waiting time, bunker consumption, operating costs, and greenhouse gas emissions. Conventional congestion mitigation often relies on infrastructure expansion, which requires substantial investment and long implementation periods. This study aims to develop a Mixed Integer Linear Programming (MILP) model that synchronizes LPG vessel arrival with jetty availability through optimal vessel speed selection to minimize bunker costs while reducing carbon emissions. A MILP optimization model was developed using operational data from Terminal LPG Tanjung Sekong, Indonesia. The model incorporates jetty capacity, vessel schedules, sailing time, processing time, fuel consumption, bunker prices, and vessel compatibility constraints to determine whether each vessel should operate at service speed or slow-steaming speed. Results show that the proposed model reduces bunker costs by USD 46,675/month, decreases jetty waiting time by 3.26 days/month, and lowers carbon emissions by 221.7 tCO₂/month. These findings demonstrate that synchronizing vessel arrival with terminal readiness provides a practical operational alternative to infrastructure expansion while supporting maritime decarbonization.