Knowledge-based scheduling in flexible manufacturing systems: An integration of pattern-directed inference and heuristic search |
| |
Authors: | MICHAEL J SHAW |
| |
Affiliation: | Decision and Information Sciences Group, Department of Business Administration , University of Illinois at Urbana-Champaign , Champaign, IL, 61820, USA |
| |
Abstract: | This paper presents a knowledge-based scheduling approach based on the problem-solving techniques developed in artificial intelligence. The approach is based on three key techniques. The first is the pattern-directed inference technique to capture the dynamic nature of the scheduling environment. The second is the non-linear planning technique to coordinate manufacturing processes and resource assignments. The third technique is the A? search algorithm to expedite the searching procedure. It models the scheduling process by state-space transitions; the job routing is obtained through selecting a sequence of scheduling operators guided by heuristics. Keeping track of the manufacturing system by a symbolic world model, this approach is adaptive to such environmental changes as new job arrivals and machine breakdowns, suitable for making real-time scheduling decisions. |
| |
Keywords: | |
|
|