교수진
김용갑
• 최종학위 및 대학 : Purdue University
• 전공 : Industrial Engineering
• 강의과목 :
- 화물운송론
- Advanced AI Applications in Global Logistics
- Vehicle routing and optimization
- International Logistics Information Systems
상세약력
중앙대학교 경영경제대학 국제물류 학과 조교수
서울시 동작구 흑석동 84, 310관 1051호
연구실: (+82) 2 820 - 5438
E-mail: yonggabkim@cau.ac.kr
Linkedin: https://www.linkedin.com/in/yonggabkim/
Education
Ph.D. in Industrial Engineering, Purdue University, USA, 2025
B.S. in Business Administration, Chung-Ang University, Korea, 2019
Employment
Assistant Professor
Department of International Logistics, Chung-Ang University, Seoul, South Korea
Mar 2026 - Present
Senior Data Scientist
Walmart Global Tech (Applied AI, Middle Mile Transportation Optimization Team), Sunnyvale, CA, USA
Feb 2025 - Feb 2026
⦁ The team previously won 2023 Franz Edlman award, "Load Planner" Product, loading and routing truck algorithm for Walmart.
Paper: https://pubsonline.informs.org/doi/abs/10.1287/inte.2023.0093
Video: https://youtu.be/MGNvEZZ3qPw?si=3YX-OKCVDngsdZRx
⦁ Improved and maintained the Load Planner system, enhancing performance of large-scale truck loading and routing optimization.
Technical Graduate Intern
Intel Corporation, Hillsboro, OR, USA
May 2022 - Aug 2023
Research Field
물류 및 운송 최적화 (Logistics & Transportation Optimization)
차량 경로 계획 및 스케줄링 (Vehicle Routing & Scheduling)
물류 시스템을 위한 머신러닝 및 메타휴리스틱 (Machine Learning & Metaheuristics for Logistics Systems)
라스트마일 및 미들마일 물류 시스템 (Last-mile & Middle-mile Logistics Systems)
Papers
⦁ Kim, B.,
Kim, Y., Choi, J., Jun, S., & Shin, Y. (2026). Alleviation of OHT Vehicle Congestion in Semiconductor FAB with Dynamic Link Weight Control: A Reinforcement Learning Approach.
International Journal of Production Research. (Accepted for publication)
doi.org/10.1080/00207543.2026.2656773
⦁ Kim, Y., Khir, R., & Lee, S. (2025). Enhancing Genetic Algorithm with Explainable Artificial Intelligence for Last-Mile Routing. IEEE Transactions on Evolutionary Computation. 10.1109/TEVC.2025.3562243
⦁ Kim, Y., Jeong, H. Y., & Lee, S. (2024). Drone delivery problem with multi-flight level: Machine learning based solution approach. Computers & Industrial Engineering,
110565. doi.org/10.1016/j.cie.2024.110565
⦁ Kim, B., Kim, Y., & Lee, S. (2024). Decentralised protocols for autonomous mobile robots in material handling: Inductive learnings from centralised controller.
International Journal of Production Research, 1–27. doi.org/10.1080/00207543.2024.2376213
⦁ Jeong, H. Y., Kim, Y., Lee, S., Moreland, J., & Zhou, C. (2023). Disruption propagation and repair response in interdependent system: Network model and simulation
approach. Simulation Modelling Practice and Theory, 124, 102730. doi.org/10.1016/j.simpat.2023.102730
Research Projects
2024
Autonomous Mobile Robot (AMR) Logistics Optimization
⦁ Project funded by MOTIE (Korea), Technology Innovation Program No. 20019178.
⦁ Supported simulation models and system analysis to optimize AI-driven AMR route planning and material handling.
2023
Wafer Demand & Tool Installment Optimization | Intel Corporation
⦁ Technical Graduate Internship; Developed Mixed-Integer Linear Programming models in CPLEX to optimize factory tool installments and simulate capacity expansion
scenarios.
2020
Network Disruption and Repair Response Simulation
⦁ Project sponsored by Naval Surface Warfare Center (NSWC).
⦁ Supported network disruption simulations and machine learning-based repair agent management systems to improve automated recovery protocols.
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