The 14th Annual AIMMS-MOPTA Competition is coming!
As part of the Modeling and Optimization: Theory and Applications (MOPTA) conference hosted by Lehigh University, this year’s challenge is to optimize scheduling for hospital operating rooms (OR).
Considering the massive overload on hospitals worldwide during the COVID-19 pandemic, this problem hits close to home for hospital management professionals. More than ever, they look to improve OR utilization, surgical care, and quality, while minimizing operational costs.
In this problem scenario, you’ll solve an elective surgery planning (ESP) problem in flexible ORs, where same-day emergency cases are also accommodated. Construct a plan to assign cases from a waiting list to available OR surgery blocks with the surgery start times assigned. Your team’s goal is to develop an efficient scheduling method that managers can use in practice.
You’ll need to consider:
- costs related to performing or delaying elective surgeries
- costs related to OR overtime and idle time
- costs related to surgery waiting times
- costs related to canceling scheduled surgeries to accommodate emergency surgeries
View full details of the competition here:
Submissions are due by May 15, 2022.
Teams of at most three students can participate. The team leader must be a graduate student, though the other members of the team can be advanced undergraduate students. Each member of the team must be registered as a full-time student at a recognized educational institution during the Spring term of the 2021-2022 Academic Year. Students with any background are eligible. Collaboration between students from different departments is strongly encouraged.
- Winning team: $1200 to the team, and a certificate for each team member.
- Second place team: $600 to the team, and a certificate for each team member.
- Third place team: $300 to the team, and a certificate for each team member.
Also, the highest-ranked finalist that used AIMMS as the software platform to solve the case will be awarded an additional $1000 in prize money.