Dr Eun-Seok Kim
Senior Lecturer in Operations Management; Programme Director for MSc International Business
Email: firstname.lastname@example.org Telephone: +44 (0)20 7882 2351Room Number: Room 4.28b, Francis Bancroft Building, Mile End CampusOffice Hours: Tuesday 2.00pm - 3.00pm; Thursday 3.00pm - 4.00pm
- Programme Director for MSc International Business
- Member of the Department of Business Analytics and Applied Economics
Dr Eun-Seok Kim is a Senior Lecturer (Associate Professor) in Operations Management at Queen Mary, University of London. He has BSc, MSc and PhD degrees in Operational Research from KAIST (Korea Advanced Institute of Science and Technology), South Korea. Before joining Queen Mary, he was a Senior Lecturer in Operations Management and Programme Leader in MSc Global Supply Chain Management at Middlesex University.
- BUS002: Operations Management
- BUS260: Quantitative Analytics
- BUSM103: Dissertation for International Business
- Methodologies: Mathematical Programming, Combinatorial Optimisation, Stochastic Analysis.
- Applications: Operations and Supply Chain Management
Dr Kim’s main research interest falls within the field of operations and supply chain management specialising in combinatorial optimisation and scheduling theory. He is also interested in applications of operational research, especially optimisation, to various problem areas including telecommunication and actuarial science.
Centre and Group Membership:
- Member of the Centre for Globalisation Research (CGR)
- Kazemi, A., E.-S. Kim and M.-H. Kazemi, "Identifying and prioritizing delay factors in Iran’s oil construction projects", To appear in International Journal of Energy Sector Management.
- Asimit, A.V., T. Gao, J. Hu and E.-S. Kim (2018), “Optimal Risk Transfer: Numerical Optimisation for Actuarial Applications”, North American Actuarial Journal, 22(3), 341 – 364. (ABS 2)
- Eun, J., C. S. Sung and E.–S. Kim (2017), “Maximizing total job value on a single machine with job selection”, Journal of the Operational Research Society, 68, 998 – 1005. (SSCI, ABS 3)
- Asimit, A.V., V. Bignozzi, K.C. Cheung, J. Hu and E.-S. Kim (2017), “Robust and Pareto Optimality of Insurance Contracts”, European Journal of Operational Research, 262(2), 720 – 732. (SCIE, ABS 4)
- Asimit, A. V., A. M. Badescu, S. Haberman and E.–S. Kim (2016), “Efficient Risk Allocation within a Non-life Insurance Group under Solvency II Regime”, Insurance: Mathematics and Economics, 66, 60-76. (SSCI, ABS 3)
- Kim, E.–S. and C. A. Glass (2015), “Perfect periodic scheduling for binary tree routing in wireless networks”, European Journal of Operational Research, 247(2), 389-400. (SCIE, ABS 4)
- Kim, E.–S. and D. Oron (2015), “Minimizing total completion time on a single machine with step improving jobs”, Journal of the Operational Research Society, 66(9), 1481-1490. (SSCI, ABS 3)
- Kim, E.–S. and C. A. Glass (2014), “Perfect periodic scheduling for three basic cycles”, Journal of Scheduling, 17(1), 47-65. (SCIE, ABS 3)
- Kim, E.–S. and D. Oron (2013), “Multi-Location production and delivery with job selection”, Computers and Operations Research, 40(5), 1461-1466. (SCIE, ABS 3)
- Kim, E.–S. and D. Oron (2013), “Coordinating multi-location production and customer delivery”, Optimization Letters, 7(1), 39-50. (SCIE)
- Kim, E.–S. (2011), “Scheduling of uniform parallel machines with s-precedence constraints”, Mathematical and Computer Modelling, 54(1-2), 576-583. (SCIE)
- Kim, E.–S and I.–S. Lee (2011), “Integrated inventory-distribution planning in a (1:N) supply chain system with heterogeneous vehicles incorporated”, International Journal of Management Science, 17(2),1-22.
- Kim, E.–S. and M. E. Posner (2010), “Parallel machine scheduling with s-precedence constraints”, IIE Transactions, 42(7), 525-537. (SCI, ABS 3)
- Kim, E.-S., C. S. Sung and I–S. Lee (2009), “Scheduling of parallel machines to minimize total completion time subject to s-precedence constraints”, Computers and Operations Research, 36(3), 698-710. (SCIE, ABS 3)
Areas of Supervision Expertise:
Dr Eun-Seok Kim welcomes prospective doctoral students with a research interest in applications of operational research, especially optimisation, to various problem areas including logistics and supply chains. Students with background in mathematics, computer science, or industrial engineering are particularly welcome to apply.