Integrating Constraint Programming Scheduling into an AI Planner

OPTIC is a state of the art piece of research software designed to allow computers to autonomously plan complex tasks, such as construction projects, rail timetables and other planning and scheduling tasks. Currently, OPTIC handles the scheduling process using a technique known as Mixed Integer Programming (MIP). In this project, the aim will be to integrate a new, alternative mechanism for performing the scheduling process, known as Constraint Programming (CP). With the help of expertise at the University of Toronto, this new approach will significantly improve on OPTIC’s ability to schedule certain types of problems, by hybridising the scheduling approach between MIP and CP techniques.

Faculty Supervisor:

Christopher Beck

Student:

Partner:

King's College London

Discipline:

Computer science

Sector:

Education

University:

University of Toronto

Program: