Tag: optimization

Optimization is an act, process, or methodology of making something as fully perfect or effective as possible. Almost everything can be improved, so optimization’s relevance spans to almost every business or process to make it operate more efficiently and effectively. Optimization employs mathematical models to discover more efficient ways to control and manage systems, ranging from radiation treatments to data centers and power networks. Optimization researchers at WID solve systems-level problems in emerging science and engineering applications by using optimization technologies in an integrated, interdisciplinary, and collaborative fashion. This includes finding solutions to problems that are the most cost-effective or achieve the highest performance under given constraints by maximizing desired elements and minimizing the undesired elements. Optimization models promise better process planning that can be tied to and offered by social, economic, and financial systems. Certain social and political constraints have caused optimization to go largely unexplored, as have methods for translating plans into policy. We hope to draw on collaborations with communications experts, political scientists, sociologists, economists, behavioral scientists, and business professionals to further leverage optimization’s potential for boosting efficiencies and improving systems that reach into all corners of our lives. Learn more about Optimization at WID. It is a key component of WID's Data Science Hub.

Alberto Del Pia

Alberto Del Pia

Associate Professor

  • WID Faculty

Design of exact and approximate algorithms for mixed-integer optimization problems

Lih-Sheng (Tom) Turng

Consolidated Papers Foundation Chair, Fellow of ASME, SME, and SPE

  • WID Faculty

Bridging engineering and life sciences for manufacturing of cell-/tissue-based therapeutic products

Jim Luedtke

Jim Luedtke

Professor

  • Discovery Fellow

Design of methods for solving discrete and stochastic optimization problems.

Stephen Wright

Steve Wright

George B. Dantzig Professor of Computer Sciences

  • Discovery Fellow

Optimization algorithms with applications to data analysis and other areas.

Michael Ferris

Michael Ferris

John P. Morgridge Chair in Computer Sciences
Jacques-Louis Lions Professor of Computer Sciences
Director of Data Science Hub

  • WID Faculty

Optimization methods and data modeling for large scale problems in science, engineering and economics

2016 Publications

2016 publications from our faculty and fellows during their time at WID are listed below. Please see each publication for additional information. View Additional Publications:

2015 Publications

2015 publications from our faculty and fellows during their time at WID are listed below. Please see each publication for additional information. View Additional Publications:

Graduate Studies at WID

Graduate students at WID partake in a highly collaborative work environment and develop new approaches to push the boundaries of their fields. With opportunities in the Institute’s many labs, graduate students study a variety of topics, ranging from data science and visualization to tissue engineering, nanomedicine, omics, and complex systems. …