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Subject to: Ted Ralphs
Manage episode 415920236 series 3000652
Dr. Ted Ralphs received his Ph.D. in Operations Research from Cornell University in 1995. He is a professor in the Department of Industrial and Systems Engineering (ISE) at Lehigh University and is co-founder and director of Lehigh's Laboratory for Computational Optimization Research at Lehigh (COR@L). He is also co-founder and board member of the COIN-OR Foundation, a non-profit foundation promoting the development of open source software for operations research, as well as the project manager for a variety of projects hosted in the COIN-OR open source software repository. He is the area editor for Software Tools at the INFORMS Journal on Computing and the area editor for Data, Software, and Computation at Operations Research. He is a Fellow of INFORMS. His research interests include theoretical aspects of discrete optimization, such as duality and complexity theory; development of a variety of methodologies for solving a range of discrete optimization problems, such as those with multiple levels/stages or multiple objectives; development of parallel search algorithms; development of open source software; and applications of discrete optimization.
96 episoder
Manage episode 415920236 series 3000652
Dr. Ted Ralphs received his Ph.D. in Operations Research from Cornell University in 1995. He is a professor in the Department of Industrial and Systems Engineering (ISE) at Lehigh University and is co-founder and director of Lehigh's Laboratory for Computational Optimization Research at Lehigh (COR@L). He is also co-founder and board member of the COIN-OR Foundation, a non-profit foundation promoting the development of open source software for operations research, as well as the project manager for a variety of projects hosted in the COIN-OR open source software repository. He is the area editor for Software Tools at the INFORMS Journal on Computing and the area editor for Data, Software, and Computation at Operations Research. He is a Fellow of INFORMS. His research interests include theoretical aspects of discrete optimization, such as duality and complexity theory; development of a variety of methodologies for solving a range of discrete optimization problems, such as those with multiple levels/stages or multiple objectives; development of parallel search algorithms; development of open source software; and applications of discrete optimization.
96 episoder
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