Article ID Journal Published Year Pages File Type
381314 Engineering Applications of Artificial Intelligence 2008 7 Pages PDF
Abstract

The criterion of total weighted completion time occurs as a sub-problem of combinatorial optimization problems in such diverse areas as scheduling, container loading and storage assignment in warehouses. These applications often necessitate considering a rich set of requirements and preferences, which makes constraint programming (CP) an effective modeling and solving approach. On the other hand, basic CP techniques can be inefficient in solving models that require inference over sum type expressions. In this paper, we address increasing the solution efficiency of constraint-based approaches to cumulative resource scheduling with the above criterion. Extending previous results for unary capacity resources, we define the COMPLETIONmCOMPLETIONm global constraint for propagating the total weighted completion time of activities that require the same cumulative resource. We present empirical results in two different problem domains: scheduling a single cumulative resource, and container loading with constraints on the location of the center of gravity. In both domains, the proposed constraint propagation algorithm out-performs existing propagation techniques.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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