Boris Goldengorin, Ph.D.
Department of Information Systems and Decision Science
Office: Business Center 475
- Ph.D., University of Groningen; The Netherlands
- Ph.D., Institute of Standardization, Moscow, Russia
- D.Sc., Institute of System Analysis, Russian Academy of Sciences; Moscow, Russia
- M.S., University of Electronics and Mathematics, Russia
- M.S., Riazan Radio Engineering University, Russia
Prof. Sc.D., Dr., Dr. Boris Goldengorin is the inventor and author of data correcting and tolerance based algorithms applied to many problems in Operations Management, Supply Chain Management, Quantitative Logistics, Industrial Engineering and Stock Market Analysis. He is an author of more than 100 papers published in top international journals including Operations Research, Management Science, European Journal of Operational Research, The Journal of Operational Research Society, Computers & Operations Research, Computers & Mathematics with Applications, Computational Management Science, Applied Soft Computing and many others. Dr. Goldengorin published five monographs, two textbooks and an editor of five books. He is an Associate Editor for Journal of Global Optimization, Journal of Combinatorial Optimization, and Journal of Computational and Applied Mathematics. Dr. Goldengorin has been involved in the preparation of a $4 MM mega grant to establish an international research lab on algorithms and technologies for network analysis (http://nnov.hse.ru/en/latna/). He is affiliated with Advanced Marketing Models Company (http://ammodelsinc.com/) in New York (USA). Prof. Goldengorin taught worldwide from middle school programs up to PhD levels and supervised more than 100 BSc, MSc, and PhD students in the Netherlands, Germany, United Kingdom, Kazakhstan, Russia, Ukraine, and United States.
Center on data correcting and tolerance based algorithms applied to combinatorial optimization problems among them the asymmetric traveling salesman, capacitated vehicle routing (with time windows, pick up and delivery, periodical, and randomly generated demands), capacitated allocation (including p-median, cell formation in industrial engineering, algebra of multidimensional BIG DATA aggregation) problems, as well as sequencing and scheduling problems. His recent research is concentrated on algorithmic proofs of the optimality for the given solution in combinatorial optimization. Another direction of his research interests is represented by applications of theory and algorithms to submodular (supermodular) maximization (minimization) problems in machine learning including text summarization, coverage of sensor networks, clustering, maximum a posteriori (MAP) decoding in graphical models. Some directions of Dr. Goldengorin’s research activities can be found in books on amazon.com https://www.amazon.com/Boris-Goldengorin/e/B00AR073TE
Concentrated from general courses in elementary mathematics for middle and high schools (covering arithmetic, pre-algebra, algebra 1, numeration systems, number theory, and statistics) through linear algebra, graph theory, mathematical logic, and discrete mathematics at the college level. Professor Goldengorin’s research interests are reflected in teaching introductory management science (operations research) and business analytics courses as well as MS and PhD level courses in big and multi-dimensional data aggregation, combinatorial optimization, algorithms and data structures, quantitative logistics, scheduling and sequencing.
Goldengorin, B. (2018). Optimization Problems in Graph Theory. In Honor of Gregory Z. Gutin’s 60th Birthday. 341.
Goldengorin, B. (2016). Optimization and Its Applications in Control and Data Sciences. In Honor of Boris Polyak’s 80th Birthday. 115. 507.
Goldengorin, B., Aleskerov, ., & Pardalos, . (2014). Clusters, Orders, and Trees: Methods and Applications. In Honor of Boris Mirkin’s 70th Birthday. 92. 386.
Karapetyan, D., Goldengorin, B., & . (2018). Conditional Markov Chain Search for the Simple Plant Location Problem improves upper bounds on twelve Körkel-Ghosh instances. Springer. 139. 123—147.
Goldengorin, B., Krushinsky, D., & . (2017). Linear Assignment Problems in Combinatorial Optimization.. 130. 183—216.
Refereed Journal Articles
Ahmadi, E., Goldengorin, B., Suer, G., Mosadegh, H., ., & . (2018). A hybrid method of 2-TSP and novel learning-based GA for job sequencing and tool switching problem. 214–229.
Goldengorin, B., Qiu, Y., Wang, L., Fang, X., Pardalos, M., ., ., & . (2018). Formulations and Branch-and-Cut Algorithms for Production Routing Problems with Time Windows. 14(8), 669-690.
Goldengorin, B., Turkensteen, . M., Malyshev, . D., Pardalos, . P., ., & . (2017). The reduction of computation times of upper and lower tolerances for selected combinatorial optimization problems. Journal of Global Optimization. 68(3), 601--622.
Goldengorin, B., Pei, J., Liu, X., Fan, w., Pardalos, P., Migdalas, A., Yang, S., ., ., ., ., & . (2016). Minimizing the makespan for a serial-batching scheduling problem with arbitrary machine breakdown and dynamic job arrival. The International Journal of Advanced Manufacturing Technology. 86(9), 3315-3331.
Goldengorin, B., Malyshev, D. S., Pardalos, P. M., Zamarayev, V. A., & . (2015). A tolerance-based heuristic approach for the weighted independent set problem. Journal of Combinatorial Optimization. 29. 433–450.
Goldengorin, B., Zilinskas, J., Pardalos, P. M., ., & . (2015). Pareto-optimal front of cell formation problem in group technology.. Journal of Global Optimization. 61. 91-108.
Goldengorin, B., Pei, J., Fan, W., Pardalos, P., Liu, X., Yang, S., ., & . (2015). Preemptive scheduling in a two-stage supply chain to minimize the makespan. Optimization Methods and Software. 30(4), 727–747.
Goldengorin, B., Jager, G., Dong, C., Molitor, P., Richter, D., & . (2014). Backbone Based TSP Heuristics for Large Instances. Journal of Heuristics. 20(1), 107–124.
Goldengorin, B., Batsyn, M., Maslov, E., Pardalos, P., ., & . (2014). Improvements to MCS algorithm for the maximum clique problem. Journal of Combinatorial Optimization. 27(2), 397–416.
Goldengorin, B., Vizgunov, A. N., Kalyagin, V. A., Koldanov, A. P., Pardalos, P. M., & . (2014). Network approach for the Russian stock market.. Computational Management Science. 11(1), 45–55.
Goldengorin, B., Batsyn, M., Pardalos, P., Sukhov, P., & . (2014). Online heuristic for the preemptive single machine scheduling problem of minimizing the total weighted completion time.. Optimization Methods and Software. 29(5), 955-963.
Research in Progress
"Implementation and Computational Study of New Algorithms for the Job Sequencing and Tool Switching Problem"
An unified reduction of the single machine scheduling problems minimizing different objective functions, namely, the total weighted completion time, the total weighted tardiness, maximum lateness, makespan, weighted number of tardy jobs, total weighted earliness, as well as the total number of tool switching or their linear and convex combinations) for the finite number of preempted jobs with arbitrary weights, release and due dates, processing times to the Linear Assignment type problems will be incorporated in a Data Correcting Type Algorithms with tolerance based branching rules.
"Predicting Students Retention of Merrick School of Business"
Based on justivied decision variables clustered into demographic and academic varibles we will incorporate a new academic variable - instructors evaluations with the purpose to elaborate a system approach to student retention including several promising directions for future research.