Optimization: Purposes, Uses, and Importance
Optimization is an act, process or methodology of making something as fully perfect or effective as possible (dictionary definition). 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. Working at UW–Madison’s Optimization group, researchers 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.
Why optimization at WID?
Drawing from the talented faculty, scientists and students at the university, WID’s Optimization group operates as a fulcrum to the interdisciplinary enterprise, in that each of its successes carries direct benefits outside the computer sciences and mathematics disciplines from which our techniques have developed. Moreover, the lessons learned in our planned collaborations are likely to improve future partnerships whether the subject and variables are drawn from ecology, medicine, agriculture, engineering or genetics. While optimization techniques have wide applicability, we focus on four areas with domain experts:
- Understand strengths and weaknesses of the application and/or model
- Create core optimization methodologies needed to solve the problem(s)
- Develop new algorithms and software, as needed
- Implement new algorithms on appropriate computational platforms
What’s new in optimization?
Podcast: Optimization research at WID