Data is cleansed allowing a selection of technique for the disposition of incomplete data, and rule generation is performed allowing a selection of technique for the induction of knowledge formulated as patterned rules. See advisor Zbigniew Ras for latest version.
Improved schedules mean a more efficient production planning process.
Our framework is a software system of ML and AI modules with deductive search components and inductive learning components for updating and utilizing a knowledge base of heuristic rules learned from routings of categorical jobshop and flowshop problems. A learning mode updates a knowledge base and a solution mode utilizes the production rules for scheduling improvement where, with one technique the rules specify criteria for the order of machine selections to generate a sequence-order of bottleneck machines. See advisor Haldun Aytug for current research.