Dr. Anurag Agarwal

Title: Professor

Area of Interest: Information Systems/Decision Sciences

Phone: 941-359-4522

Curriculum Vitae: CV

Email: agarwala@sar.usf.edu

Office: C217

Professor Agarwal’s teaching interests lie broadly in the field of Analytics, Data Mining and Information Systems. In the last five years, he has taught courses such as Big Data Analytics, Business Analytics, Business Statistics, Operations Management, Information Systems in Organizations, Systems Analysis and Design, Database Systems, Programming Languages and Decision Support Systems. His primary research interests are in developing heuristics and metaheuristics for a variety of combinatorial optimization problems. He also does research in the use of artificial intelligence techniques such as Neural Networks and Genetic Algorithms for Data Mining and other problems. He has published in journals such as INFORMS Journal on Computing, Naval Research Logistics, European Journal of Operational Research, Omega – the International Journal of Management Science, Computers and Operations Research, Annals of Operations Research and Information Technology and Management. He serves on the editorial board of Information Technology and Management and Enterprise Information Systems. He has worked in industry as Systems Analyst and Programmer. Prior to joining USF, Professor Agarwal served on the faculty of University of Florida.


Agarwal, A., Colak, S. and Erenguc, S.S., “Metaheuristic Methods for the Resource Constrained Project Scheduling Problem,” Invited Chapter in: Handbook on Project Management and Scheduling, Volume 1, Schwindt, C. and Zimmermann, J. (eds) Springer, (2015), 57-76.

Shatskikh, A., Yang, W., Cobanoglu, C., and Agarwal, A., "Are Consumers Ready for Mobile Payment? An Examination of Consumer Acceptance of Mobile Payment Technology in Restaurant Industry", FIU Hospitality Review, (2015) 31(4), Article 6, link for the paper.

Ngo, F., Govindu, R. and Agarwal, A., "Assessing the Predictive Utility of Logistic Regression, Classification and Regression Tree, Chi-Squared Automatic Interaction Detection and Neural Network Models in Predicting Inmate Misconduct" American Journal of Criminal Justice, published online, May 2014 (10.1007/s12103-014-9246-6)

Agarwal, A.,Colak, S., Deane, J. and Rakes, T., “The Task Scheduling Problem: A NeuroGenetic Approach,” Journal of Business and Economics Research, 2014, 12(4), 327-334.

Deane,J. and Agarwal, A., “Scheduling Online Advertisements to Maximize Revenue under Non-Linear Pricing,”Journal of Computer Information Systems, 2013, 53(2), 85-92

Deane,J. and Agarwal, A., “Neural,Genetic and Neurogenetic Approaches For Solving the 0-1 Multidimensional Knapsack Problem,”International Journal of Management Information Systems, 2013, 17(1), 43-54.

Kasap, N. and Agarwal, A., “Augmented Neural Networks and Problem-Structure Based Heuristics for the Bin-Packing Problem,” International Journal of Systems Science, 2012, 43(8), 1412-1430.

Deane, J., and Agarwal, A, “Scheduling Online Advertisements to Maximize Revenue Under Variable Display Frequency,” OMEGA, The International Journal of Management Science, 2012, 40(5), 562-570.

Deane, J., Rakes, T. and Agarwal, A., "Designing Content Distribution Networks for Optimal Cost and Performance,” Information Technology and Management, 2012, 13(1), 1-15.

Agarwal, A., Ramamoorti, S. and Jayaraman, V., “Decision Support Systems for Strategic Conflict Resolution,” International Journal of Management Information Systems, 2011, 15(4), 13-30.

Agarwal, A., Colak, S., and Erenguc, S.S., “A Neurogenetic Approach for the Resource-Constrained Project Scheduling Problem,” Computers and Operations Research, 2011, 38(1), 44-50.

Agarwal, A., Colak, S., and Deane, J., "NeuroGenetic Approach for Combinatorial Optimization: An Exploratory Analysis," Annals of Operations Research, 2010, 174(1),185-199.

Agarwal, A. and Jayaraman, V., "Scheduling to Minimize Penalties for Suppliers in Integrated Supply Chains," International Journal of Manufacturing Technology and Management, 2010, 19 (1/2), 68-81.