Houston, Texas - October 25th, 2017
On Tuesday, October 24th, at the 2017 INFORMS Annual Conference held in Houston, TX, a team from Lehigh University using Gurobi was awarded the top international prize in Operations Research, the Daniel H. Wagner prize, for their work developing the Inmate Assignment Decision Support System (IADSS).
Assigning inmates to correctional facilities is a complex process taking into account literally dozens of factors relating to the inmate, such as criminal history, demographic characteristics, and mental and physical health needs, as well relating to the prison system, such as facility utilization levels, support program availability, and existing inmate characteristics at each facility. Good assignments are important for both the inmate, since they can result in a lower chance of violent interactions with other inmates as well as faster access to treatment programs, and the prison system, since it can reduce staff workload and the number of prison transfers.
The application the Lehigh team developed took five years to create but saved the Pennsylvania Prison System $3 million in just the first year of use. It has reduced the number of incidences of inmate violence, reduced transfer rates and staff workload, and has also reduced the time it takes for inmates to get access to treatment programs. What literally took a staff of seven a full week to do is now done in just a few minutes on a daily basis by the application. The team's process and results are detailed in the paper submitted for their winning entry, "The Inmate Assignment and Scheduling Problem and its Application in the PA Department of Corrections."
The problem is modeled as a Mixed Integer Linear Optimization problem where the objective is a hierarchically weighted sum of six different objectives including: penalizing violations of assignment criteria, not exceeding capacity constraints and minimizing wait times for treatment programs. The model contains about 30,000 binary about 200 integer variables, and has about 25,000 constraints. Gurobi is used as the engine with the solve terminated when it reaches a small predetermined optimality gap. In just a few minutes, Gurobi is able to provide a high quality solution and the application is now in daily use at the Pennsylvania Department of Corrections.
The project participants included:
You can read the INFORMS press release on this year's Wagner Prize winner here. The picture above includes State Senator Lisa Boscola, and was taken in the Pennsylvania Senate when the team was recognized by the Pennsylvania House and Senate.
Gurobi is in the business of helping companies make better decisions through the use of prescriptive analytics. In addition to providing the best math programming solver, as well as tools for distributed optimization and optimization in the cloud, the company is known for its outstanding support and no-surprises pricing.
The Gurobi Optimizer is a state-of-the-art solver for linear programming (LP), quadratic programming (QP), quadratically constrained programming (QCP), mixed-integer linear programming (MILP), mixed-integer quadratic programming (MIQP), and mixed-integer quadratically constrained programming (MIQCP). Gurobi was designed from the ground up to exploit modern architectures and multi-core processors, using the most advanced implementations of the latest algorithms. Founded in 2008, Gurobi Optimization is based in Houston, TX.