Mehmet Sevkli

Dr. Mehmet Sevkli earned his Ph.D. in Industrial Engineering. His primary teaching interests include management science, business and data analytics, predictive and prescriptive analytics, operations management, and optimization. His research focuses on developing metaheuristic approaches to combinatorial optimization problems such as job scheduling, facility location, and vehicle routing. He has published numerous papers in leading academic journals and presented his work at national and international conferences.

• OPS 301 - Survey of Operations & Supply Management
• OPS 401 - Operations Planning and Control
• OPS 375 - Management Science
• BAN 211 - Statistics for Business II
• BAN 402 - Prescriptive Analytics
• BAN 618 - Advanced Business Analytics
• MBA 791 - Business Analytics

• Ph.D., Industrial Engineering, Istanbul Technical University, 2005

• Optimization using Gurobi
• Machine Learning Algorithms
• Metaheuristics for Combinatorial Optimization Problems
• Multi-Criteria Decision Making
• Operations Scheduling

• Unal, Y.Z., Sevkli, M., Uysal, O., & Turkyilmaz, A. (2021). A new approach to fleet assignment and aircraft routing problems. Transportation Research Procedia, 59, 67–75.
• Kibria, G.M.D., & Sevkli, M. (2021). Application of deep learning for credit card approval: A comparison with two machine learning techniques. International Journal of Machine Learning and Computing, 11(1), 286–290.
• Basti, M., & Sevkli, M. (2015). An artificial bee colony algorithm for the p-median facility location problem. International Journal of Metaheuristics, 4(1), 91–113.
• Ciftci, M.E., & Sevkli, M. (2015). A new hub and spoke system proposal: A case study for Turkey's aviation industry. Journal of Air Transport Management, 47, 190–198.
• Zaim, S., Sevkli, M., Camgöz-Akdag, H., Demirel, O.F., Yayla, A.Y., & Delen, D. (2014). Use of ANP weighted crisp and fuzzy QFD for product development. Expert Systems with Applications, 41(9), 4464–4474.
• Sevkli, M., Mamedsaidov, R., & Camci, F. (2014). A novel discrete particle swarm optimization for p-median problem. Journal of King Saud University – Engineering Sciences, 26(1), 11–19.
• Sevkli, M., Oztekin, A., Uysal, O., Torlak, G., Turkyilmaz, A., & Delen, D. (2012). Development of a fuzzy ANP based SWOT analysis for the airline industry in Turkey. Expert Systems with Applications, 39(1), 14–24.
• Eker, O.F., Camci, F., Guclu, A., Yilboga, H., Sevkli, M., & Baskan, S. (2011). A simple state-based prognostic model for railway turnout systems. IEEE Transactions on Industrial Electronics, 58(5), 1718–1726.
• Torlak, G., Sevkli, M., Sanal, M., & Zaim, S. (2011). Analyzing business competition by using fuzzy TOPSIS method: An example of Turkish domestic airline industry. Expert Systems with Applications, 38(4), 3396–3406.
• Sevkli, M. (2009). An application of the fuzzy ELECTRE method for supplier selection. International Journal of Production Research, 48(12), 3393–3405. https://doi.org/10.1080/00207540902814355
• Tasgetiren, M. F., Liang, Y., Sevkli, M., & Gencyilmaz, G. (2007). A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem. European Journal of Operational Research, 177(3), 1930-1947. https://doi.org/10.1016/j.ejor.2005.12.024
• Sevkli, M., Lenny Koh, S. C., Zaim, S., Demirbag, M., & Tatoglu, E. (2007). An application of data envelopment analytic hierarchy process for supplier selection: a case study of BEKO in Turkey. International Journal of Production Research, 45(9), 1973–2003. https://doi.org/10.1080/00207540600957399