Announcement
2015 Spring KSEA Monthly Multidisciplinary Seminar Speaker Sang Jin Kweon, a Ph.D. student in the intercollege dual-title degree graduate program in Industrial Engineering and Operations Research at Penn State will present “Optimal Location of Liquefied Natural Gas (LNG) Refueling Stations on the Pennsylvania Turnpike” on Thursday, March 5th, at 7 PM in 209 IST. Food and drinks will be served. All are welcome.
Title
Optimal Location of Liquefied Natural Gas (LNG) Refueling Stations on the Pennsylvania Turnpike
Abstract
Increases in the price of oil and concerns about the finite nature of reserves, coupled with increasing awareness of the environmental damage caused by the burning of traditional fossil fuels, stimulated interest in alternative, renewable sources of energy. As one of the alternative-fuels, Liquefied Natural Gas (LNG) is considered an attractive option for commercial long-haul trucks due to its low CO2 emissions as well as its low price. With its benefits, more and more long-haul trucks are switching to liquefied natural gas (LNG). Recognizing the increased spotlight on LNG for fleets, the Pennsylvania Turnpike Commission (PTC) requested a feasibility study on the use of LNG as alternative fuel for the commercial trucking industry along the Turnpike. As a part of the research work performed in the feasibility study, in this talk, we present a new mathematical model that optimally locates p LNG refueling stations on a tree network, such as the PA Turnpike, so as to maximize the number of truck trips covered.
More About Sang Jin Kweon
Ph.D. Candidate
The intercollege dual-title degree graduate program in Industrial Engineering and Operations
Penn State University
Education
M.S., Industrial Engineering, Penn State University, 2013
B.S., Industrial Engineering, Yonsei University, Korea, 2006
Research Interests
Sang Jin Kweon’s work has centered around the applied optimization, and his main research interests are the location-allocation problem in the transportation sector and the robust optimization problem for the supply chain.