Multi-objective optimization of petroleum product logistics in Eastern Indonesia region

The transportation sector is one of the largest fuel consumers and pollutant contributors worldwide. The International Maritime Organization predicts that the greenhouse gas (GHG) emissions from transportation will be increasing significantly until 2050, driven by the growth in global maritime trade. Managing logistics distribution routes is considered a possible approach for controlling GHG emissions. This study aims to implement a green logistics concept in the logistics distribution of petroleum products-gasoline, kerosene, and diesel-in eastern Indonesia, whose supply sources are refineries located in Balikpapan and Kasim. A multi-objective approach is used to implement the green logistics concept. Multi-objective optimization is conducted using the AIMMS software to optimize a logistics system consisting of a multi-depot, multi-product, and heterogeneous fleet. The optimization is performed to determine the best logistics route and the amount of products delivered using certain types of fleets to minimize transportation cost and GHG emissions using constant speed. In addition, this study also investigates the effect of variable speed on cost and CO2 emissions. For the constant speed case, the distribution routes obtained for the minimizing cost scenario tends to maximize the utilization of transit terminals while in the minimizing emissions scenario tends to deliver directly to the distribution centers, so the route decision in multi-objective optimization scenario is combination of the two. The multi-objective optimization results an 11% cost reduction and a 17% GHG emission reduction compared with the current values. The comparison between constant and variable speed reveals that the variable speed is preferred to constant speed as it gives lower emissions with slight changes in cost. (C) 2021 The Authors. Production and hosting by Elsevier B.V.

Automated summary

This study aims to implement green logistics concept in eastern Indonesia to reduce transportation cost and GHG emissions. Multi-objective optimization was conducted, resulting in an 11% cost reduction and a 17% GHG emission reduction. The study also found that variable speed is preferred over constant speed in terms of lower emissions with slight changes in cost.