Reasoning about opportunistic schedules

The scheduling of jobs and resources In a manufacturing environment is important because o f its basic impact on production costs, but is difficult because of the problems of combinatorial complexity and executwnal uncertainty. Scheduling suffers from combinatorial complexity because there are a very large number of schedules which can be generated f o r a set of jobs and resources, but there is no good way to choose between the options prior to execution. Scheduling is complicated by executional uncertainty in that unforeseeable events will almost certainly occur to disrupt any particular schedule once execution commences. This paper describes a novel approach to scheduling which overcomes these two difficulties. Implementation of the approach requires a new representation for schedules and techniques for knowledge-based reasoning about this representation. The issues involved in performing the knowledge-based reasoning are described and illustrated by examples drawn from the domain of robotic assembly.