From sports scheduling to transporting goods, or portfolio optimization to cancer treatments, integer programs are used to create optimal solutions and policies. Companies, governments and society have all substantially benefited from integer programming solutions in their efforts to improve real world policies.
Current methods are unfortunately limited in their ability to solve integer programs even when the most advanced technology is used. In such scenarios, decision makers are left with suboptimal strategies, which can impair desired results.
Todd Easton specializes in discrete optimization with an emphasis in integer programming and graph theory. His current research aims to find novel techniques to solve integer programs to better facilitate industry leaders in making timely and accurate decisions.
IMPROVING SOLUTION TIME OF INTEGER PROGRAMS
By utilizing graphs and hypergraphs, Easton's research group has identified new methods to allow more integer programs to be solved.
These methods include creating new cutting planes, developing new branching procedures and generating polynomial time algorithms to lift variables.
RESEARCH OBJECTIVE - Develop novel methods to improve the computational effort required to solve integer programs.
1. Develop novel cutting plane methodologies.
2. Create fast algorithms that improve the solution time of integer programs.
ADDITIONAL RESEARCH INTERESTS
- Integer programming and graph theory
- Discrete optimization
- Effective teaching techniques