MINLP 2014
Mixed-Integer Nonlinear Programming

   

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Chair:
  Nick Sahinidis
Co-Chair:
  Ignacio Grossmann


Mixed-Integer Nonlinear Programming 2014

The workshop is scheduled to take place on June 2-5, 2014 at
Carnegie Mellon University, Pittsburgh, PA

Mixed-integer nonlinear programming is a powerful modeling paradigm that has been employed by engineers, economists, and operations researchers to model a wealth of decision-making applications that involve discrete decisions and nonlinearities. Over the past two decades, algorithm developers have been increasingly drawn to MINLP and the challenges encountered at the intersection of combinatorial optimization and nonlinear optimization. As the international MINLP community has grown, several workshops on mixed-integer nonlinear programming took place recently. As part of this series, in 2014, the MINLP workshop is organized by Ignacio Grossmann and Nick Sahinidis at Carnegie Mellon University. Participants of MINLP 2014 are expected to discuss challenges and opportunities in the field of mixed-integer nonlinear optimization, as well as to review progress made on algorithmic, computational, and applications aspects.

This meeting is sponsored by the Mathematical Optimization Society and held in cooperation with the Society for Industrial and Applied Mathematics and the SIAM Activity Group on Optimization. The SIAM representative is Nick Sahinidis.