A new approach for modelling uncertainty in expert systems knowledge bases

The current paradigm of modelling uncertainty in expert systems knowledge bases using Certainty Factors (CF) has been critically evaluated. A way to circumvent the awkwardness, non-intuitiveness and constraints encountered while using CF has been proposed. It is based on introducing Data Marks for askable conditions and Data Marks for conclusions of relational models, followed by choosing the best suited way to propagate those Data Marks into Data Marks of rule conclusions. This is done in a way orthogonal to the inference using Aristotelian Logic. Using Data Marks instead of Certainty Factors removes thus the intellectual discomfort caused by rejecting the notion of truth, falsehood and the Aristotelian law of excluded middle, as is done when using the CF methodology. There is also no need for changing the inference system software (expert system shell): the Data Marks approach can be implemented by simply modifying the knowledge base that should accommodate them. The methodology of using Data Marks to model uncertainty in knowledge bases has been illustrated by an example of SWOT analysis of a small electronic company. A short summary of SWOT analysis has been presented. The basic data used for SWOT analysis of the company are discussed. The rmes_EE SWOT knowledge base consisting of a rule base and model base have been presented and explained. The results of forward chaining for this knowledge base have been presented and critically evaluated

Declarativity in modelling and problem solving

The paper discusses a new trend in the modelling software for combinatorial and mixed combinatorial-continuous decision problems. The trend, aiming at solving those problems by the simple activity of properly describing them, is best exemplified by a constantly inereasing spectrum of Constraint Logic Programming (CLP) languages. The first such language was Prolog. After a short historical survey concentrating mainly on Prolog, main characteristics of a modern, commercially successful CLP language - CHIP - are presented, discussed and illustrated. The CLP approach to problem solving is compared with traditional Operation Research approaches

A Two-stage approach for an optimum solution of the car assembly scheduling problem. Part 2. CLP solution and real-world example

A Constraint Logic Programming (CLP) tool for solving the problem discussed in Part 1 of the paper has been designed. It is outlined and discussed in the paper. The program has been used for solving a real-world car assembly scheduling problem

A Two-stage approach for an optimum solution of the car assembly scheduling problem Part 1. Problem statement, solution outline and tutorial example

A new approach to solving realistic car assembly scheduling problems for mixed model assembly line is presented. It is proposed to decompose the problem into two subproblems: 1) a sequencing problem that generates admissible car sequences fulfilling capacity constraints for all car models in the production plan, 2) a scheduling problem that determines an admissible car sequence with shortest makespan. The details of this approach are illustrated by a simple numerical example