Amar Rachman

Petrol Delivery Assignment with Multi-Product, Multi-Depot, Split Deliveries and Time Windows

The purpose of this study is to solve a planning problem faced by Pertamina, a state-owned Oil and Gas company in Indonesia, dealing with the delivery of petrol products. Based on Petrol Station Replenishment Problem (PSRP), a fleet of tank-trucks with different capacities has been assigned to deliver two petrol products from two depots with split deliveries and time windows to a set of petrol stations in the working area. The Tabu Search (TS) algorithm has been used to solve this problem. The problem consists of jointly determining the fleet assignment and of designing delivery routes to petrol stations to satisfy the orders using the available resources with the minimum total travel cost for delivery.

Oil fuel delivery optimization for multi product and multi depot: the case of petrol station replenishment problem (PSRP)

With the Oil and Gas Law No. 22 of 2001, national and foreign private enterprises can invest in all sectors of Oil and Gas in Indonesia. In anticipation of this free competition, Pertamina, as a state-owned enterprises, which previously had monopolized the oil and gas business activities in Indonesia, should be able to improve services as well as the efficiency in order to compete in the free market, especially in terms of cost efficiency of fuel distribution to gas station (SPBU). To optimize the distribution activity, it is necessary to design a scheduling system and its fuel delivery routes daily to every SPBU. The determination of routes and scheduling delivery of fuel to the SPBU can be modeled as a Petrol Station Replenishment Problem (PSRP) with the multi-depot, multi-product, time windows and split deliveries, which in this study will be completed by the Tabu Search algorithm (TS). This study was conducted in the area of Bandung, the capital of West Java province, which is a big city and the neighboring city of Jakarta, the capital city of Indonesia. By using the fuel delivery data for one day, the results showed a decrease of 16.38% of the distance of the route compared to the current conditions, which impacted on the reduction of distribution costs and decrease the number of total trips by 5.22% and 3.83%.