The manufacturing environment is complex and quickly changing, and its management involves multiple production goals and many constraints in solving problems. Job shop scheduling is a typical problem of this area, and shares the above properties. Although this problem is complex, it is generally not ill-structured. For these reasons, an AI approach, especially the employment of search techniques, is useful to cope with this problem. This paper proposes a hierarchical constraint-directed search method for application in actual scheduling problems. In this method, constraints are classified as interactive or absolute according to their interrelationships. Based on this, a three stage search is carried out to find a solution which successively satisfies the constraints. Furthermore, this method utilizes the knowledge of scheduling experts to facilitate problem solving. The above approach is applied to the scheduling of berth assignments as an example of an actual problem. A computerized scheduling system is developed using a frame-based language, and is evaluated by comparing its solution performance with that of a non-hierarchical constraint satisfaction method and that of scheduling experts. The proposed system shows good performance results, being superior to the non-hierarchical method and equal to the scheduling experts in most cases. The hierarchical constraint-directed approach thus shows promise for use in solving real world production management problems.