Operations Research and Applied Optimization Lab

최적화 연구실

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최적화 연구실

The mission of the Operations Research and Applied Optimization Lab is to conduct high-quality academic research while addressing real industrial and government problems. Research activities are focused on the use and development of advanced computer software to analyze and optimize performance measures of actual systems. The lab's faculty participants have a unique combination of expertise and experiences that allow them to address complex problems in logistics, transportation, and renewable energy systems, stochastic modeling and analysis of manufacturing systems, facility layout and location, and network design and optimization.


최적화, 교통, 물류, 공유경제, 에너지, 알고리즘


인공지능, 기계학습, 강화학습, 디지털 트윈

Research Keywords and Topics

• Optimization problems in the sharing economy, logistics and transportation sectors, and their effects on energy sustainability and environment
• Logistics problems related to energy systems in the areas of facility location and allocation; inventory management; supply chain logistics; graph theory; dynamic programming; multiple criteria optimization; queueing theory; markov decision processes
• Public policies for welfare economics and spatial equity
• Application of operations research to the fundamental research that forms the foundation for smart grid and smart & connected communities
• Data mining and big data analytics to analyze and formulate drivers/riders behavior patterns
• Polynomial-time algorithms to search and optimize vehicle detour options
• Analysis of potential effects of autonomous vehicles in logistics and transportation areas

Research Publications

Kweon, S. J.*, Hwang, S. W., and Ventura, J. A. 2017. “A continuous deviation-flow location problem for an alternative-fuel refueling station on a tree-like transportation network.” Journal of Advanced Transportation, 1-20.

Ventura, J. A.*, Kweon, S. J., Hwang, S. W., Tormay, M., and Li, C. 2017. “Energy policy considerations in the design of an alternative-fuel refueling infrastructure to reduce GHG emissions on a transportation network.” Energy Policy, 111, 427-439.

Hwang, S. W., Kweon, S. J., and Ventura, J. A.* 2017. “Locating alternative-fuel refueling stations on a multi-class vehicle transportation network.” European Journal of Operational Research, 261 (3), 941-957.




  • NA. 수학
  • NA05. 응용수학
  • NA0503. 수리계획법/최적화이론


  • 기타 분야
  • 060000. 국가기술지도(NTRM) 99개 핵심기술 분류에 속하지 않는 기타 연구


  • 고효율화기술
  • 수송효율성 향상
  • 332. 지능형교통, 물류기술


  • IT 분야
  • 차세대 네트워크 기반
  • 010214. 기타 네트워크기술