Archive for category Ports, Logistics and Supply Chain

SEMS Research Highlights 2015: Enabling the Adoption of Alternative Fuel Vehicles – An Approach to Refueling Station Spatial Placements

Refueling station accessibility for more cleaner and greener energy is one of the most important factors in the adoption of alternative fuel vehicles.


Image Courtesy of Radar Pena

If the refueling station is not strategically located, people will be hesitant to adopt the new alternative fuel (such as gas, hydrogen or other type of alternative fuel).
Due to the importance of locations,  researcher in System Engineering, Modeling, and Simulation lab of Universitas Indonesia develop an operations research-based spatial-model to determine ideal refueling station locations. Early results has delivered a whopping gain up to 96% demand coverage, while at same time maintained profitability in each individual location.

The model was develop in three stages: demand mapping, spatial simulation and financial screening.

First stage is determining how many refueling stations are needed to cover potential demand within the scope. This is done through a series of calculations: total vehicles converted are multiplied by each vehicle’s fuel demand, subtracted by the amount of existing alternative fuel supply (if some refueling stations already exist), and then divided by an individual station’s capacity. Through these calculations, a number of stations needed to be built can be obtained.

In the second stage, multiple variables are used as input to reflect real-world conditions in a geographic information system-based spatial model. These variables include spatial data, such as the locations of distributed potential demand, already-existing alternative refueling stations, and candidate locations to build the new refueling stations, as well as non-spatial data, like the daily capacity of each refueling station and the maximum distance car owners are willing to travel to reach a station. The model then uses a location-allocation technique—the ‘maximize capacitated coverage’ approach—to determine the ideal locations for every refueling stations. These locations cover the most demand possible while subjecting to the capacity of individual stations.

The final stage is financial screening of the chosen locations. Three economic metrics are used to determine profitability: the NPV, IRR, and payback period. The demand in each location chosen, obtained through the spatial model, is entered into a simple financial model of a refueling station’s operations to reveal the three economic metrics. Afterwards, a final analysis is conducted to determine other alternatives to reach demand points not yet covered, or to replace unprofitable locations.

In this study, the researchers focused on the adoption of natural gas vehicles by public transportation fleets in DKI Jakarta, as the case study. There were four scenarios used, based primarily on the types of candidate locations (to simulate ease of implementation) and the simulated traffic conditions. The resulting locations show a range of 79-96% coverage, with the lower numbers found in traffic jam scenarios. To boost coverage and replace unprofitable locations, there were 2 possible alternatives: constructing stand-alone refueling stations (not constrained by candidate locations) and deploying mobile refueling units (MRUs).

This work has implications for various types of alternative fuel vehicles, not just limited to natural gas. Refueling stations are capital-heavy infrastructures regardless of fuel type, especially for new, still growing vehicle types. The approach used is replicate-able and adjustable for other situations to improve the adoption process.

This research was conducted by Aziiz Sutrisno, Akhmad Hidayatno, Dio Aufa Handoyo, Eka Nugraha Putra

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SEMS Research Highlights 2015: Improving the Soekarno Hatta International Airport Utilization as the Main Gate of Indonesia

With the steady economic growth for the last ten years in Indonesia has made people mobility across the nation is at all time high. This is why, that most airport in Indonesia is operated more than its capacity. Soekarno Hatta International Airport (SHIA) is currently operated twice than its designed capacity. This problem has strong influence to the level of service of the airport, which next could lead to the decreasing of the passenger’s satisfaction (Yan, Shieh, & Chen, 2002). The challenges of the airport operator are to do further investment and to optimize the utilization of current ability.

Based on a research done by Redaksi Angkasa (2014), the current maximum traffic capacity of SHIA is 72 landing-takeoff traffics per one hour. They found that this still could be improved till 86 landing-takeoff traffics per one hour. Another standing point is more than 40% flights in SHIA is being parked in the remote area. The remote area is basically the aircraft parking area, located far away from the terminal building.

SEMS was trying to solve this problem, because we believe the better service from gated flights could maintain the image of SHIA as the main gate of Indonesia. There are some researches already studied about this topic. Bennel, Mesgarpour, & Potts (2011) have done a research focus on developing an optimization model. The objective of the study is to maximize the number of flights. Another research was done by integrating the runway allocation and gate assignment problem to maximize the number of flights could be accommodated in an airport (Nahry, T., & Y.J., 2013). Additionally, SEMS saw a research opportunity not to focus on operator’s perspective only, but also on the passenger’s perspective such as minimizing flight tardiness and minimizing passenger walking distance in the terminal.

This research is basically focusing on developing an optimization combination model of runway and gate assignment. The output of this research is to generate to most optimal runway and gate schedule concerns on 4 objectives, such as maximizing landing-takeoff traffics, minimizing flight tardiness, minimizing flights being parked in remote area, and minimizing passenger walking distance in airport. The model is done using the Genetic Algorithm Optimization Approach. The Genetic Algorithm it self is a metaheuristics algorithm, functioning to generate the best solution in a certain solution space of a certain problem.

Using the model, a significant reduction on un-gated flight has been achieved which reduce the traveling distance of the passenger.

This research is Conducted by Gede Arya Satya Dharma, Aziiz Sutrisno, Armand Omar Moeis, and Akhmad Hidayatno

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Beer Game Simulation at Astra Honda Motor AHM

In order to introduce the basic concept of Supply Chain Management for all its Dealers, PT Astra Honda Motor AHM asked SEMS Lab to conduct Beer Game Simulation. The Beer Game Serious Simulation Gaming (SSG) is perfect interactive way to have a common understanding of supply chain challenges (With of course No Beer drinking involved). Approximately 67 dealers were trained on September 10, 2014 at PT AHM Tipar Cakung. The facilitators team was lead by Mr. Hariyanto Salim MSIE, CSCP that consist of 1 Game Master, and 10 Game Companion for each Game Board.
Even though it is a classic game, the beer game was still an eye opener for all the participants, who are all practitioner and very expert in the field.


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