| Article ID: | iaor1988100 |
| Country: | United Kingdom |
| Volume: | 27 |
| Issue: | 1 |
| Start Page Number: | 101 |
| End Page Number: | 118 |
| Publication Date: | Jan 1989 |
| Journal: | International Journal of Production Research |
| Authors: | Parlar M. |
| Keywords: | inventory, artificial intelligence |
This paper discusses the development of a knowledge-based expert system (EXPIM) which can identify and recommend up to 30 production-inventory models. The user (manager) is asked a sequence of questions regarding the problem situation. The system uses backward-chaining to identify what is the correct model to use given the situation described by the user. The paper also discusses the general methodology for building expert systems in management science for the purpose of identifying models in other areas, such as queueing theory and local theory.