Résumé :
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In this paper, our case-based approach, implemented in the system called CABINS, is presented for capturing a human expert's preferential criteria about schedule quality and control knowledge to speed up problem solving. By iterative schedule repair, CABINS improves the quality of sub-optimal schedules, and during the process CABINS utilizes past repair experiences for repair tactic selection and repair result evaluation. It is empirically demonstrated that CABINS can optimize a schedule along objectives captured in its case base and improve the efficiency of optimization process while preserving the quality of a resultant schedule.
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