Automated model construction: A logic based approach

Attempts to integrate Artificial Intelligence (AI) techniques into Decision Support Systems (DSS) have received much attention in recent years. Significant among these has been the application of knowledge-based techniques to support various phases of the modeling process. This paper describes a logic based approach to mechanically construct Linear Programming (LP) models from qualitative problem specifications and illustrates it in the context of production, distribution and inventory planning problems. Specifically, we describe the features of a first-order logic based formal language called PM which is at the heart of an implemented knowledge-based tool for model construction. Problems specified in PM define a logic model which is then used to generate problem-specific inferences, and as input to a set of logic programming procedures that perform model construction.

[1]  Fred Glover,et al.  Network Application in Industry and Government , 1977 .

[2]  Ramayya Krishnan.  PDM: a knowledge-based tool for model construction , 1989, [1989] Proceedings of the Twenty-Second Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track.

[3]  Arthur M. Geoffrion,et al.  An Introduction to Structured Modeling , 1987 .

[4]  Matthias Jarke,et al.  Domain-Specific Dss Tools for Knowledge-Based Model Building , 1985, Decis. Support Syst..

[5]  L. Zurich,et al.  Operations Research in Production Planning, Scheduling, and Inventory Control , 1974 .

[6]  D. Klingman,et al.  An Optimization Based Integrated Short-Term Refined Petroleum Product Planning System , 1987 .

[7]  A. Charnes,et al.  Management Models and Industrial Applications of Linear Programming , 1961 .

[8]  Saul I. Gass,et al.  Managing the modeling process: a personal reflection , 1987 .

[9]  Darwin Klingman,et al.  Mathematical Optimization--A Successful Tool for Logistics Problems. , 1981 .

[10]  Fred Glover,et al.  An Integrated Production, Distribution, and Inventory Planning System , 1979 .

[11]  Thomas L. Magnanti,et al.  Applied Mathematical Programming , 1977 .

[12]  Robert Fourer,et al.  Modeling languages versus matrix generators for linear programming , 1983, TOMS.

[13]  Arnoldo C. Hax,et al.  Production and inventory management , 1983 .

[14]  Frederic H. Murphy,et al.  The Science and Art of Formulating Linear Programs , 1987 .

[15]  Brian W. Kernighan,et al.  AMPL: a mathematical programming language , 1989 .

[16]  Frederic H. Murphy,et al.  Computer-assisted Formulation of Linear Programs , 1986 .

[17]  Daniel R. Dolk,et al.  A generalized model management system for mathematical programming , 1986, TOMS.

[18]  Stephen Leroy Loy,et al.  An experimental investigation of a graphical problem-structuring aid and nominal group technique for group decision support systems , 1986 .

[19]  Frederick Hayes-Roth,et al.  Building expert systems , 1983, Advanced book program.

[20]  Ramayya Krishnan,et al.  Knowledge-based aids for model construction , 1987 .

[21]  Jeffrey D. Ullman,et al.  Principles of Database Systems , 1980 .

[22]  A. M. Geoffrion,et al.  Multicommodity Distribution System Design by Benders Decomposition , 1974 .

[23]  David A. Kendrick,et al.  The Planning of Investment Programs in the Steel Industry , 1978 .

[24]  Robert C. Leachman,et al.  A general framework for modeling production , 1989 .

[25]  David R. Dowty,et al.  Introduction to Montague semantics , 1980 .

[26]  Pai-Chun Ma.  An intelligent approach towards formulating linear programs , 1988 .

[27]  Jay W. Cohen,et al.  Structured modeling , 1982, Winter Simulation Conference.