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Research

Table of contents

  1. Research Areas
    1. Supply Chain Management
    2. Data Mining
  2. Graduate Students Supervised
    1. In Progress
    2. Graduated
  3. Publications
    1. Journal Articles
    2. Conference Proceedings and Book Chapters
    3. Edited Books and Special Issues
  4. Funding
    1. Grants in Progress
    2. Completed

Research Areas

My research interests lie primarily in the fields of supply chain management and data mining spanning decision analytics and mathematical optimization problems.

Supply Chain Management

I work on inventory control under demand and supply uncertainty. These decision problems are ubiquitous in healthcare and humanitarian aid operations. I have also studied various mathematical optimization problems in production and service systems, including scheduling, lot sizing, routing, and pricing.

Data Mining

My research involves combinatorial optimization approaches in numerous subdomains of data mining, including sequential testing, multi-instance learning, and time series analysis. In addition, I have applied supervised learning approaches to the toxicological evaluation of nanoparticles and interpreting EEG data.


Graduate Students Supervised

In Progress

  • Deniz N. Yoltay (2nd year Ph.D.)
  • Serkan Ürkmez (3rd year Ph.D.)
  • Buket İpek Akbal (1st year M.S.)
  • Cem Y. Yıldız (1st year M.S.)

Graduated

  • Ph.D.
    • Tonguç Yavuz, Fall 2021, Assistant Professor at Bilgi University
    • Samira Saedi, Spring 2013, Assistant Director of Healthcare System Engineer at Texas Children’s Hospital
    • Mohammad H. Poursaeidi, Spring 2013, Senior Research Engineer at Intel Corporation
  • M.S.
    • Şeyma Gözüyılmaz, Fall 2019, Ph.D. Student at Sabancı University
    • İbrahim Edhem Sakarya, Spring 2019, Ph.D. Student at Eindhoven University of Technology
    • Ahmet Emir Tuzcu, Spring 2019, Control and Automation Engineer at Eczacıbaşı ESAN
    • Onur Şimşek, Spring 2019, Product Manager at n11.com
    • Gizem Atasoy, Summer 2018, Ph.D. Student at University of Illinois at Chicago
    • Cem Deniz Çağlar Bozkır, Spring 2018, Senior Analytics Consultant at KoçDigital
    • Ayşenur Betül Çengil, Summer 2017, Ph.D. Student at the University of Arkansas
    • Büşra Tüfekci, Spring 2016, Prodution Planning Supervisor at Beş A
    • Andrea Viacaba, Fall 2011, Global Supply Chain Analyst II at Mary Kay Global
    • Smita (Sethi) Jain, Fall 2011, Data Analyst at Wyndham Destinations
    • Savya K. Ramesh, Fall 2010, Industrial Engineering Consultant at Eton System

Publications

Journal Articles

  1. I. E. Sakarya and O. E. Kundakcioglu, “Multi-instance learning by maximizing the area under receiver operating characteristic curve,” Journal of Global Optimization, forthcoming.
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  1. C. D. C. Bozkir, O. E. Kundakcioglu, and A. C. Henry, “Hospital service levels during drug shortages: Stocking and transshipment policies for pharmaceutical inventory,” Journal of Global Optimization, vol. 83, pp. 565-584, 2022.
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  1. S. Korkmaz, O. E. Kundakcioglu, and O. Sivrikaya, “A fluid approximation for the single-leg fare allocation problem with nonhomogeneous Poisson demand,” Journal of Revenue and Pricing Management, vol. 21, pp. 81-96, 2022.
  1. O. Simsek and O. E. Kundakcioglu, “Cost of fairness in agent scheduling for contact centers,” Journal of Industrial and Management Optimization, vol. 18, no. 2, pp. 873-896, 2022.
  1. S. Azizi, C. D. C. Bozkir, A. C. Trapp, O. E. Kundakcioglu, and A. K. Kurbanzade, “Aid allocation for camp-based and urban refugees with uncertain demand and replenishments,” Production and Operations Management, vol. 30, no. 12, pp. 4455-4474, 2021.
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  1. S. Gozuyilmaz and O. E. Kundakcioglu, “Mathematical optimization for time series decomposition,” OR Spectrum, vol. 43, pp. 733-758, 2021.
  1. M. Önal, O. E. Kundakcioglu, and S. Sethi, “An EOQ model with deteriorating items and self-selection constraints,” Optimization Letters, vol. 14, pp. 1491–1518, 2020.
  1. T. Yavuz, O. E. Kundakcioglu, and T. Ünlüyurt, “Exact and heuristic approaches to detect failures in failed k-out-of-n systems,” Computers and Operations Research, vol. 112, 104752, 2019.
  1. N. R. Barshes, S. Saedi, J. Wrobel, P. Kougias, O. E. Kundakcioglu, and D. G. Armstrong, “A model to estimate cost-savings in diabetic foot ulcer prevention efforts,” Journal of Diabetes and Its Complications, vol. 31, no. 4, pp. 700–707, 2017.
  1. B. Balcik, C. D. C. Bozkir, and O. E. Kundakcioglu, “A literature review on inventory management in humanitarian supply chains,” Surveys in Operations Research and Management Science, vol. 21, no. 2, pp. 101–116, 2016.
  1. M. Önal, A. Yenipazarli, and O. E. Kundakcioglu, “A mathematical model for perishable products with price- and stock-dependent demand,” Computers and Industrial Engineering, vol. 102, pp. 246–258, 2016.
  1. S. Saedi, O. E. Kundakcioglu, and A. C. Henry, “Mitigating the impact of drug shortages for a healthcare facility: An inventory management approach,” European Journal of Operational Research, vol. 251, no. 1, pp. 107–123, 2016.
  1. M. H. Poursaeidi and O. E. Kundakcioglu, “Robust support vector machines for multiple instance classification,” Annals of Operations Research, vol. 216, no. 1, pp. 205–227, 2014.
  1. W. van den Heuvel, O. E. Kundakcioglu, J. Geunes, H. E. Romeijn, T. Sharkey, and A. P. M. Wagelmans, “Integrated market selection and production planning: Complexity and solution approaches,” Mathematical Programming, vol. 134, no. 2, pp. 395–424, 2012.
  1. G. Pyrgiotakis, O. E. Kundakcioglu, P. M. Pardalos, and B. M. Moudgil, “Raman spectroscopy and support vector machines for quick toxicological evaluation of Titania nanoparticles,” Journal of Raman Spectroscopy, vol. 42, no. 6, pp. 1222–1231, 2011.
  1. O. E. Kundakcioglu, O. Seref, and P. M. Pardalos, “Multiple instance learning via margin maximization,” Applied Numerical Mathematics, vol. 60, no. 4, pp. 358–369, 2010.
  1. P. M. Pardalos and O. E. Kundakcioglu, “Classification via mathematical programming,” Applied and Computational Mathematics, vol. 8, no. 1, pp. 23–35, 2009.
  1. G. Pyrgiotakis, O. E. Kundakcioglu, K. Finton, P. M. Pardalos, K. Powers, and B. M. Moudgil, “Cell death discrimination with Raman spectroscopy and support vector machines,” Annals of Biomedical Engineering, vol. 37, no. 7, pp. 1464–1473, 2009.
  1. O. Seref, O. E. Kundakcioglu, O. Prokopyev, and P. M. Pardalos, “Selective support vector machines,” Journal of Combinatorial Optimization, vol. 17, no. 1, pp. 3–20, 2009.
  1. O. E. Kundakcioglu and T. Ünlüyurt, “Bottom-up construction of minimum-cost AND/OR trees for sequential fault diagnosis,” IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol. 37, no. 5, pp. 621–629, 2007.

Conference Proceedings and Book Chapters

  • S. Saedi and O. E. Kundakcioglu, Handbook of Combinatorial Optimization, 2nd Ed., P. M. Pardalos, D.-Z. Du, and R. Graham, Eds., Springer, 2013, ch. Combinatorial optimization in data mining, pp. 595–630.
  • M. H. Poursaeidi, M. Samorani, and O. E. Kundakcioglu, "Offshore Wind Farm Layout Optimization: What is the Hype?," in Proceedings of the Industrial and Systems Engineering Research Conference, ID: 952, 2013.
  • A. Viacaba, M. H. Poursaeidi, and O. E. Kundakcioglu, "Natural gas price forecasting via selective support vector regression," in Proceedings of the Industrial and Systems Engineering Research Conference, ID: 645, 2012.
  • O. E. Kundakcioglu and P. M. Pardalos, Clustering Challenges in Biological Networks, W. A. Chaovalitwongse, S. Butenko, and P. M. Pardalos, Eds., World Scientific, 2009, ch. The complexity of feature selection for consistent biclustering, pp. 257–266.
  • O. E. Kundakcioglu and P. M. Pardalos, Lectures on Global Optimization. American Mathematical Society, 2009, Fields Institute Communications Series, P. M. Pardalos and T. F. Coleman, Eds., vol. 55, ch. Optimization in biomedical research, pp. 155–182.
  • O. E. Kundakcioglu and S. Alizamir, Encyclopedia of Optimization, second edition, C. A. Floudas and P. M. Pardalos, Eds., Springer, 2009, ch. Generalized assignment problem, pp. 1153–1162.
  • O. Seref, O. E. Kundakcioglu, and M. Bewernitz, Encyclopedia of Healthcare Information Systems, N. Wickramasinghe and E. Geisler, Eds., IDEA Group Inc., 2008, ch. Support vector machines in neuroscience, pp. 1283–1293.
  • O. Seref and O. E. Kundakcioglu, "Multiple instance classification with relaxed support vector machines," in Proceedings of the 3rd INFORMS Workshop on Data Mining and Health Informatics, J. Li, D. Aleman, and R. Sikora, Eds., 2008.
  • O. E. Kundakcioglu and P. M. Pardalos, "A branch and bound algorithm for multiple instance classification," in Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications (MLMTA), H. R. Arabnia and Y. Mun, Eds., vol. 2, 2008, pp. 865–869.
  • O. Seref, O. E. Kundakcioglu, and P. M. Pardalos, "Selective linear and nonlinear classification," in Data Mining and Mathematical Programming, ser. CRM Proceedings and Lecture Notes, P. M. Pardalos and P. Hansen, Eds., vol. 45, American Mathematical Society, 2008, pp. 211–234.
  • O. Seref, C. Cifarelli, O. E. Kundakcioglu, P. M. Pardalos, and M. Ding, "Detecting categorical discrimination in a visuomotor task using selective support vector machines," in Proceedings of the 2007 International Conference on Bioinformatics & Computational Biology (BIOCOMP), H. R. Arabnia, M. Q. Yang, and J. Y. Yang, Eds., vol. 2, 2007, pp. 580–587.
  • O. E. Kundakcioglu, K. Bulbul, T. Ünlüyurt, K. Kilic, and O. Ercetin, "Minimum power multicasting with delay bound constraints in ad hoc wireless networks," in New Trends in Computer Networks, ser. Advances in Computer Science and Engineering: Reports. Imperial College Press, 2005, pp. 252–263.

Edited Books and Special Issues

  • H. Yang, O. E. Kundakcioglu, and D. Zeng, "Healthcare data analytics," Information Systems and e-Business Management, vol. 13, no. 4, pp. 595–597, 2015.
  • H. Yang and O. E. Kundakcioglu, "Healthcare intelligence: Turning data into knowledge," IEEE Intelligent Systems, Trends & Controversies, vol. 29, no. 3, pp. 54–56, 2014.
  • H. Yang, D. Zeng, and O. E. Kundakcioglu, Eds. Proceedings of the 7th INFORMS Workshop on Data Mining and Health Informatics, 2012.
  • O. E. Kundakcioglu, T. Ünlüyurt, and G. Ulusoy, "Preface," Optimization Letters, vol. 6, no. 6, pp. 1035–1037, 2012.
  • O. E. Kundakcioglu, M. Sanguineti, and T. B. Trafalis, "Guest editorial," Computational Management Science, vol. 6, no. 1, pp. 1–3, 2009.
  • O. Seref, O. E. Kundakcioglu, and P. M. Pardalos, Eds., Data mining, systems analysis, and optimization in biomedicine, no. 953, American Institute of Physics, 2008.

Funding

Grants in Progress

  • PI, Coordination and Management of Uncertainty in Refugee Camp Inventory Operations, TUBITAK ARDEB 1001.
  • Researcher, Stock Replenishment and Storage Space Allocation Problem When Demand is Stock Dependent, TUBITAK ARDEB 1001, PI: M. Önal, co-PI: E. Albey.
  • PI, Industry 4.0 Applications in Flat Steel Manufacturing, TUBITAK BIDEB 2244, co-PI: O. Ozener.

Completed

  • PI, Airline Optimization and Engineering System, TUBITAK TEYDEB 1507.
  • Consultant, MeVe: Supporting Tool for the Measurement and Verification of Energy Savings Under IPMVP, TUBITAK TEYDEB 1509 – EUREKA, PI: MIR ARGE, SYLTEC, CARTIF.
  • PI, TV Commercial Broadcast Management Suite, TUBITAK TEYDEB 1507.
  • PI, Inventory Management and Transshipment Policies for Drugs with No Annual Contract in Pharmaceutical Supply Chain Planning Under Uncertainty, TUBITAK ARDEB 3501.
  • Consultant, Design and Development of Wireless Sensor Network Platform for Power Theft and Loss Detection on Overhead Lines, KOSGEB, PI: REENGEN.
  • PI, Development of an Activities Engine, EmLogis Incorporated Research Gift.
  • PI, Enhancing Student Engagement and Encouraging Participation Through Web 2.0 in an Online Version of Graduate Course in Optimization and Data Mining, University of Houston Faculty Development Initiative Program.
  • PI, Inventory Management for Perishable Medical Supplies, University of Houston Small Grants Program.
  • PI, Combinatorial Optimization in Kernel-based Learning Methods, University of Houston New Faculty Research Grant.