Hybridizing a genetic algorithm with rule-based reasoning for production planning

Scheduling problems in steelmaking are too large and complex for any one method. Our approach divides the problem into subproblems, and then combines procedural methods, a rule-based expert system, and a genetic algorithm. This strategy produces time-saving, cost-effective schedules.<
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