A hierarchical scheduling problem is considered. The hierarchy consists of five levels. Each level has an associated rule base. There are six basic input factors: (1) the priority of a job, (2) the earliness of the due date of a job, (3) the likelihood of the availability of resources for the work station, w/s(s), (4) the capability of w/s(s) to meet physical constraints, (5) the capability of w/s(s) to meet quality requirements, and (6) work in progress inventory costs. There are five consequents, one for each level: (1) suggested place of a job in the order of jobs, (2) the suggested place of w/s(s) in the order of w/s(s), (3) the (current) suggested place of a w/s(s) in the order of w/s(s), (4) the next current, suggested place of w/s(s) in the order of w/s(s), and (5) the suggested place of the queue arrangements. Both the input factors (antecedents) and the output factors (consequents) take on linguistic terms to express the qualitative assessments of a scheduling expert within the context of the specific factor. An approximate reasoning framework, based on interval valued fuzzy sets and a search tree heuristic with similarity measures, is executed for the analysis of the hierarchical scheduling problem using a fuzzy tool box coded in LISP that interacts with KEE for the representation of the knowledge base in a frame structure. The software model is tested with real life data used in M. Fox’s ISIS model. A comparison of the two models based on tardiness measure shows that there are slight advantages to fuzzy set representation and approximate reasoning with respect to tardiness measure above and beyond the ‘user friendly’ nature of knowledge representation available with fuzzy sets.
