A generic library of problem solving methods for scheduling applications

Rajpathak, Dnyanesh; Motta, Enrico; Zdráhal, Zdeněk; Roy, Rajkumar

doi:10.1145/945649.945663

Cited by 7 publications

(11 citation statements)

References 9 publications

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“…Here, we describe the engineering of the Propose & Revise [41] method, which demonstrates how a new PSM in our library can be constructed simply by reusing and specializing Generic-Schedule. The engineering of all the PSMs in our library can be found in [56]. The P&R method [41] was originally developed to tackle the VT system for elevator configuration [40] and it was later extended to solve the production scheduling problem [42], [68].…”

Section: Engineering Of the Propose And Revise Methodsmentioning

confidence: 99%

“…This decomposition allows us to construct the new PSMs simply by reusing or specializing the tasks and methods from Generic-Schedule. A more detailed discussion of Generic-Schedule and other components of the library can be found in [55], [56]. The OCML version of Generic-Schedule can be browsed using the WebOnto environment at: http://plainmoor.open.…”

Section: A Generic Model Of Scheduling Problem Solvingmentioning

confidence: 99%

“…The space of scheduling problem-solving can be represented by means of a state-space and operators [56]. The class schedule-space indicates a problem space associated with the scheduling task and it is composed of a set of schedule states.…”

Section: Schedule Space Schedule State and State Transitionmentioning

confidence: 99%

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A generic library of problem solving methods for scheduling applications

Rajpathak

Motta

Zdráhal

et al. 2006

IEEE Trans. Knowl. Data Eng.

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How to cite: Rajpathak, D.G.;Motta, E.; Zdrahal, Z. and Roy, R. (2006). A generic library of problem solving methods for scheduling applications. IEEE Transactions on Knowledge and Data Engineering, 18 (6) pp. 815-828. For guidance on citations see FAQs. c [not recorded] Version: [not recorded]Link(s) to article on publisher's website: http://dx.doi.org/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.

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Section: Engineering Of the Propose And Revise Methodsmentioning

confidence: 99%

Section: A Generic Model Of Scheduling Problem Solvingmentioning

confidence: 99%

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A generic library of problem solving methods for scheduling applications

Rajpathak

Motta

Zdráhal

et al. 2006

IEEE Trans. Knowl. Data Eng.

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“…), task ontologies ( R ajpathak et al. , Z hao and P erry ), and application ontologies ( K auppinen et al. , A ntezana et al.…”

Section: Related Workmentioning

confidence: 99%

The Basic Formal Ontology as a Reference Framework for Modeling the Evolution of Administrative Units

Gantner

Waldvogel

Meile

et al. 2012

Transactions in GIS

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In information systems, ontologies promise advantages such as enhanced interoperability, knowledge sharing, and integration of data sources. In this article, we show that the upper ontology Basic Formal Ontology can facilitate the modeling of an evolution of administrative units. This is demonstrated by creating a spatiotemporal ontology for the administrative units of Switzerland. The ontology tackles the problem that the geometric data is typically captured by taking snapshots at regular intervals while the thematic data is continually updated. The ontology presented merges time‐stamped geometries with a formally described history of administrative units, allowing for complex spatiotemporal queries neither standard approach would support. The resulting populated knowledge base was evaluated against a set of spatiotemporal test queries. The evaluation showed that this knowledge base supports a wide range of queries on the evolution of the administrative units of Switzerland between 1960 and 2010.

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“…An ontology (Gruber 1993, Rajpathak et al 2006 provides an information model that explicitly formalises ontological commitments associated with the domain in terms of various entities and abstractions along with the properties that are associated with them. An ontology (Gruber 1993, Rajpathak et al 2006 provides an information model that explicitly formalises ontological commitments associated with the domain in terms of various entities and abstractions along with the properties that are associated with them.…”

Section: The Ivhm Ontologymentioning

confidence: 99%

Ontology-driven data collection and validation framework for the diagnosis of vehicle healthmanagement

Rajpathak

Subramania

Bandyopadhyay

2012

International Journal of Computer Integrated Manufacturing

Self Cite

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The current warranty data collection processes exhibit several data quality issues -the level of detail and precision is missing in the collected data, the semantic heterogeneity is observed and no systematic data quality validation mechanism to automatically certify the data quality. Such data cannot be translated seamlessly into the knowledge assets to perform business functions, for example, fault diagnosis. An ontology-driven structured data collection framework is proposed to acquire the necessary data in the warranty domain. The proposed framework uses the integrated vehicle health management ontology as an information model to populate necessary data acquisition fields of the framework. A novel three-dimensional data quality metric is proposed to validate the completeness, correctness and relevance of newly collected data. We also evaluate the performance of the tool by using the real-life data. The data accuracy precision after using the framework has been improved from 0.30 to 0.80, whereas the recall is improved from 0.28 to 0.70. Furthermore, the precision and recall of the tool is evaluated for the 500 real-life field failure cases and it was greater than 90% for data completeness and relevance. Throughout this paper we will use the words 'correctness' and 'accuracy' interchangeably.

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A generic library of problem solving methods for scheduling applications

Abstract: A generic library of problem solving methods for scheduling applications. IEEE Transactions on Knowledge and Data Engineering, 18(6) pp. 815-828. For guidance on citations see FAQs.

Cited by 7 publications

References 9 publications

A generic library of problem solving methods for scheduling applications

A generic library of problem solving methods for scheduling applications

The Basic Formal Ontology as a Reference Framework for Modeling the Evolution of Administrative Units

Ontology-driven data collection and validation framework for the diagnosis of vehicle healthmanagement

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