Intelligent use of Constraints for Activity Scheduling
The primary goal of this research effort was to develop a domain independent activity scheduling algorithm that would be able to handle ad-hoc constraints.
The activity scheduling problem is one of assigning tasks (activities) to objects (jobs) while adhering to time and resource constraints. Operations researchers originally had approached the problem using mathematical programming techniques. This approach, however, is poor at solving real world problems. Real World problems tend to be very large and are often too complex to represent numerically.
An algorithm is presented that is based on an heuristic search paradigm. Symbolic constraints are used to assist the search process. The scheduling problem is represented as a group of variables. Each variable has a corresponding set of possible values, called a value set. The aim is to assign each variable a value from its value set while adhering to the imposed constraints. The schedule is deemed complete as soon as the first set of variable assignments which satisfy all the constraints is obtained. The program does not make any attempts to optimize the solution.
The role of constraints in activity scheduling is examined and intuitions about constraint generation, posting & propagation are presented.
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