Robust optimization has traditionally focused on uncertainty in data and costs in optimization problems to formulate models whose solutions will be optimal in the worstcase among ...
Kedar Dhamdhere, Vineet Goyal, R. Ravi, Mohit Sing...
In the Sesame framework, we develop a modeling and simulation environment for the efficient design space exploration of heterogeneous embedded systems. Since Sesame recognizes se...
The National Airspace System (NAS) is designed to accommodate a large number of flights over North America. For purposes of workload limitations for air traffic controllers, the a...
Amitabh Basu, Joseph S. B. Mitchell, Girishkumar S...
We present a novel framework based on hidden Markov models (HMMs) for matching feature point sets, which capture the shapes of object contours of interest. Point matching algorith...
Meta-heuristics such as simulated annealing, genetic algorithms and tabu search have been successfully applied to many difficult optimization problems for which no satisfactory pro...