Issues in the Design of AI-Based Schedulers: A Workshop Report

The concatenation of these reports forms the body of this article. Abstract Based on the experience in manufacturing production scheduling problems which the AI community has amassed over the last ten years, a workshop was held to provide a forum for discussion of the issues encountered in the design of AIbased scheduling systems. Several topics were addressed including: the relative virtues of expert system, deep method, and interactive approaches, the balance between predictive and reactive components in a scheduling system, the maintenance of convenient scheduling descriptions, the application of the ideas of chaos theory to scheduling, the state of the art in schedulers which learn, and the practicality and desirability of a set of benchmark scheduling problems. This article expands on these issues, abstracts the papers which were presented, and summarizes the lengthy discussions that took place. Since its first formal business meeting in August of 1988, the American Association for Artificial Intelligence Special Interest Group in Manufacturing (SIGMAN) has held a number of workshops, three of which have been concerned with the application of AI techniques to the problem of manufacturing scheduling.