Green logistics enables the identification of optimal routes and schedules that achieve cost efficiency while substantially lowering environmental footprints. In the petroleum industry, green logistics seeks to balance multiple goals, such as minimizing transportation costs, reducing carbon emissions, and improving service levels. In this study, a multi-objective optimization (MOO) model is formulated to minimize transportation costs and optimal time for routing which consider the services, departure and travelling time for multi-component with the least amount of carbon emissions. Furthermore. The environmental impact caused by conventional and Liquefied Natural Gas (LNG) vessels will be also examined. The Ant Colony Optimization (ACO) algorithm, inspired by natural processes, is utilized for its efficiency in addressing complex routing challenges is implemented to solve a case scenario of petroleum logistics. A refinery center and eight different distribution transits in the straits of Indonesia are examined in this study and the optimal solution is determined. The results show an optimal transportation cost of USD 1,255,099.49, covering a distance of 9304.45 km and total routing time is 394.47 h while generating a minimum of 155.26 g of CO2 by using conventional vessel while obtain transportation cost of USD 289,187.74, covering a distance of 9304.45 km and total routing time is 394.47 h while generating a minimum of 0.2924 g of CO2 by using LNG vessel. The results indicate that LNG vessels are desirable to be used in petroleum maritime transportation problems. This study supports the overarching global goal of promoting sustainability, mitigating climate change impacts, and enhancing cost efficiency in the shipping of petroleum products within the industry.