COLL is doing research in the following two areas:

• Computational Optimization: Study large-scale discrete optimization problems, especially in the area of optimization under uncertainty in which discrete decision variables are included in the model, plus a wide range of applications in production and workforce planning, power scheduling, terminal operations, and evacuation planning.

• Logistics and Supply Chain Management: Study a few topics driven by industry applications such as inventory inaccuracy analysis, fleet routing and berth allocation.

COLL is also dedicated to promote optimization under uncertainty as an efficient approach to solve a wide range of real-time decision making problems and stimulate student interest in research in this area.

COLL has been supported by Federal Agencies such as National Science Foundation, Department of Defense and Department of Transportation, as well as local industries.