A hybrid optimization and knowledge-based approach to job shop scheduling

A synergetic combination of optimization and knowledge-based methods in a system of distributed architecture is presented. At the resource level, precedence-constrained operations with various levels of importance are near-optimally scheduled to minimize weighted tardiness. Violations of precedence and capacity constraints are handed by knowledge-based methods at the higher, coordination level. The net result is an effective, informative, and flexible job shop scheduling system.<
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