The U.S. Federal Communications Commission (FCC) authorizes and manages the use of the radio frequencies (“spectrum”) that Americans use for communications purposes. The demand for spectrum has increased dramatically every year as myriads of new types of devices and uses for spectrum are being developed – and demanded by consumers and businesses. The FCC was required to determine how much spectrum was available to be repurposed, how to determine channel availability for nearly 3,000 stations across the United States and Canada on as few as 28 channels, and what new channel assignments would be feasible substitutes for television broadcasters who would remain on the air after the auction. To solve these challenging problems, the FCC created two tools: (i) a distributed optimization solver to address all optimization problems, using Gurobi, combined with a set of custom heuristics and decomposition approaches to determine optimal or near optimal solutions, for each problem; and (ii) a highly customized portfolio of satisfiability solvers that determine, usually within a fraction of a second, whether a given station repacking was feasible or infeasible. The FCC’s use of optimization enabled the market to determine the maximum amount of spectrum to repurpose while giving all stations that remain on air a channel equivalent to their pre-auction channel. Importantly, these tools ultimately enabled the FCC to assign most of the remaining TV stations to their original channel, thereby significantly reducing transition costs and TV viewer inconvenience. The FCC won the 2018 Franz Edelman Competition.
The Gurobi Optimizer was the solver chosen by the team from Lehigh University that won this year’s prestigious Daniel H. Wagner Prize for Excellence in Operations Research. The team from Lehigh University was recognized for their unique new application of O.R. within the correctional system in the U.S. The project was designed to solve a costly and vexing problem for the Pennsylvania Department of Corrections – inmate assignment. The team formulated the inmate assignment problem as a Mixed Integer Linear Programming problem (MILP). This MILP model considers nearly 100 unique factors that impact the task of assigning inmates to different prisons. A complex task that used to take 7 employees a week to calculate now takes 10 minutes with the Gurobi Optimizer. Additionally, the new approach is saving a planned $3,000,000 a year.
Choose the evaluation license that fits you best, and start working with our Expert Team for technical guidance and support.
Request free trial hours, so you can see how quickly and easily a model can be solved on the cloud.