Industrial and Systems Engineering
|Office:||CORE Building, Room 212|
Honggang Wang received his Bachelor of Science degree in Power Engineering from Shanghai Jiao Tong University, Shanghai, China, in 1996, Master of Science in Manufacturing Engineering from University of Missouri-Rolla, in 2004, and Ph.D. in Industrial Engineering from Purdue University, Indiana, in 2009. He has worked as a Postdoctoral Scholar in Energy Resources Engineering at Stanford University for two years before he joined the department of Industrial and Systems Engineering at Rutgers in 2011.
Dr. Wang's research and teaching interests lie in system uncertainty modeling and analysis, stochastic optimization, operations research, and their applications in oil/gas exploration and production, shale gas production, carbon sequestration, and geothermal resources. Dr. Wang has won IBM faculty award 2012. His research has been supported by Rutgers Research Council, IBM, and Petro China.
Ph.D., 2009, Industrial Engineering, Purdue University
IBM Faculty Award, 2012
Stochastic modeling and optimization; multi-objective optimization under uncertainty; numerical simulation; operations research for petroleum, shale gas, and geothermal resources development; carbon geologic sequestration; smart grid, energy, water distribution, and environmental systems.
- Wang, H. G., "Direct zigzag search for discrete multi-objective optimization", Computer and Operations Research, in press.
- Wang, H. G., Chen, X., "Optimization of maintenance planning for water distribution network under stochastic failures", Journal of Water Resources Planning and Management, in press.
- Wang, H. G., Gong, B., "Hierarchical stochastic modeling and optimization for petroleum eld development under geological uncertainty", Computers and Industrial Engineering, 2015, 80, 23-32.
- Wang, H. G., "A zigzag search method for multi-objective optimization," INFORMS Journal on Computing, 2013, 25(4), 654-665.
- Wang, H. G., Pasupathy, R., Schmeiser, B. W., "Integer-ordered simulation optimization using R-SPLINE: retrospective search via piecewise-linear interpolation and neighborhood Enumeration," ACM Transactions on Modeling and Computer Simulation, 2013, 23(3), 1-17.
- Wang, H. G., "Retrospective optimization of mixed stochastic systems using dynamic simplex interpolation," European Journal of Operational Research, 2012, 217(1), 141-148.
- Wang, H. G., Echeverria, D., Durlofsky, L. J., \Optimal well placement under uncertainty using a retrospective optimization framework," Society of Petroleum Engineers Journal, 2012, 17(1), 112-121.