Title :
A generic library of problem solving methods for scheduling applications
Author :
Rajpathak, Dnyanesh G. ; Motta, Enrico ; Zdrahal, Zdenek ; Roy, Rajkumar
Author_Institution :
Knowledge Media Inst., Open Univ., Milton Keynes
fDate :
6/1/2006 12:00:00 AM
Abstract :
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
Keywords :
knowledge based systems; ontologies (artificial intelligence); problem solving; scheduling; generic library; generic problem-solving model; generic scheduling task ontology; knowledge modeling; problem solving methods; task-method-domain-application; Artificial intelligence; Dynamic scheduling; Job shop scheduling; Knowledge based systems; Knowledge engineering; Libraries; Manufacturing; Ontologies; Problem-solving; Resource management; Knowledge modeling; knowledge engineering; knowledge-based systems; ontologies; problem solving methods; scheduling.; task-method-domain-application modeling;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
DOI :
10.1109/TKDE.2006.85