Optimization and Learning Through Evolutionary Computation (K. Deb)
Evolutionary and classical algorithms are most often applied to find one or more high-performing solutions for an industrial problem. Such an effort takes a considerable time to formulate the resulting optimization problem, customize an existing algorithm to make it efficient to solve the problem in a reasonable computational time, and evaluate the obtained solutions for their sensitivities to parameter changes. Kalyanmoy Deb (Koenig Endowed Chair Professor at Department of Electrical and Computer Engineering in Michigan State University, USA) will present this talk at GECCO 2017 in the Evolutionary Computation in Practice track on Monday, July 17th.
In the Evolutionary Computation in Practice track, well-known speakers with outstanding reputation in academia and industry present background and insider information on how to establish reliable cooperation with industrial partners. They actually run companies or are involved in cooperations between academia and industry.