Production/Manufacturing scheduling typically involves the acquisition of user optimization preferences. The ill-structuredness of both the problem space and the desired objectives make practical scheduling problems di cult to formalize and costly to solve, especially when problem con gurations and user optimization preferences change over time. This paper advocates an incremental revision framework for improving schedule quality and incorporating user dynamically changing preferences through Case-Based Reasoning. Our implemented system, called CABINS, records situation-dependent tradeo s and consequences that result from schedule revision to guide schedule improvement. The preliminary experimental results show that CABINS is able to e ectively capture both user static and dynamic preferences which are not known to the system and only exist implicitly in a extensional manner in the case base.