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In this paper, we propose a generic library of problem-solving methods for scheduling applications. Although some attempts have been made in the past at developing the libraries of scheduling problem-solvers, these only provide limited coverage. Many lack generality, as they subscribe to a particular scheduling domain. Others simply implement a particular problem-solving technique, which may be applicable only to a subset of the space of scheduling problems. In addition, most of these libraries fail to provide the required degree of depth and precision. In our approach, we subscribe to the Task-Method-Domain-Application knowledge modeling framework which provides a structured organization for the different components of the library. At the task level, we construct a generic scheduling task ontology to formalize the space of scheduling problems. At the method level, we construct a generic problem-solving model of scheduling that generalizes from the variety of approaches to scheduling problem-solving, which can be found in the literature. The generic nature of this model is demonstrated by constructing seven methods for scheduling as an alternative specialization of the model. Finally, we validated our library on a number of applications to demonstrate its generic nature and effective support for developing scheduling applications.
Knowledge modeling, knowledge engineering, knowledge-based systems, task-method-domain-application modeling, ontologies, problem solving methods, scheduling.

D. G. Rajpathak, Z. Zdrahal, R. Roy and E. Motta, "A Generic Library of Problem Solving Methods for Scheduling Applications," in IEEE Transactions on Knowledge & Data Engineering, vol. 18, no. , pp. 815-828, 2006.
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