INTELLIGENT ASSISTANT FOR QUANTITATIVE SIMULATION MODEL GENERATION FROM IDEF3 PROCESS DESCRIPTION

RECENT ADVANCES IN THE AREA OF SIMULATION MODELING HAVE FOCUSED ON IMPROVING SIMULATION MODELING LANGUAGES. THESE ADVANCES HAVE ADDRESSED THE SEMANTIC GAP BETWEEN SIMULATION MODEL DESIGN AND AN EXECUTABLE SIMULATION PROGRAM. THEY REPRESENT IMPORTANT ADVANCES FOR IMPROVING THE PRODUCTIVITY OF SIMULATION MODELERS BUT DO LITTLE TO AID THE NON-SIMULATION TRAINED DECISION MAKER. THROUGH THISPROPOSED RESEARCH, WE HOPE TO ADVANCE THE STATE OF THE ART OF THE ACTUAL SIMULATION MODEL DESIGN. IN DOING THIS, WE HOPE TO: 1) REDUCE THE DEPENDENCY OF DOMAIN EXPERTS ON SIMULATION ANALYSTS. 2) ASSIST EXPERIENCED SYSTEMS ANALYSTS, 3) FACILITATE EFFECTIVE COMMUNICATION BETWEEN EXPERTS AND ANALYSTS, AND 4) ACCURATELY TRANSLATE SYSTEM DESIGN GOALS AND OBJECTIVES TO EXECUTABLE SIMULATION CODE. THESE GOALS WILL BE ACHIEVED BY APPLYING KNOWLEDGE BASED MODEL DESIGN METHODS TO THE SIMULATION BOTTLENECK THAT EXISTS BETWEEN DOMAIN EXPERTS AND SIMULATION ANALYSTS. THE OBJECTIVE IS TO DUPLICATE THE SKILLS USED BY THE EXPERIENCED SIMULATION ANALYST IN THE CONSTRUCTION OF SIMULATION MODELS. THESE MODELS WILL BE GENERATED FROM STRUCTURED SYSTEM DESCRIPTIONS PROVIDED BY THE DOMAIN EXPERT, USING IDEF3, AND FROM THE STATED GOALS FOR THE ANALYSIS TO BE PERFORMED.