A generic library of problem solving methods for scheduling applications

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

doi:10.1145/945645.945663

Cited by 10 publications

(14 citation statements)

References 13 publications

(10 reference statements)

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“…., P i }. The algorithm makes use of the term frequency function [29] to set the minimum frequency threshold of two to check the validity of each P i recorded in a technician verbatim. The main reason why the minimum frequency threshold is set to two because in our domain three types of technician verbatim are recorded-customer verbatim, correction verbatim, and causal verbatim, and if P i is recorded only in a single verbatim which does not have any symptoms within the word window set on the either side of P i then the algorithm does not have necessary confidence to consider P i as the valid part failure.…”

Section: Part-based Clustersmentioning

confidence: 99%

“…The history-based approach analyzes historical data captured in the faulty and the normal conditions to identify solution patterns that can be used for the case in hand. Finally, the knowledge-based approach embeds the domain-specific knowledge in a knowledgebased system in the form of ontologies [15] and the rules or problem-solving methods [13,29].…”

Section: Introductionmentioning

confidence: 99%

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A domain-specific decision support system for knowledge discovery using association and text mining

2011

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We propose a novel association and text mining system for knowledge discovery (ASTEK) from the warranty and service data in the automotive domain. The complex architecture of modern vehicles makes fault diagnosis and isolation a non-trivial task. The association mining isolates anomaly cases from the millions of service and claims records. ASTEK has shown 86% accuracy in correctly identifying the anomaly cases. The text mining subscribes to the diagnosis and prognosis (D&P) ontology, which provides the necessary domain-specific knowledge. The root causes associated with the anomaly cases are identified by discovering frequent symptoms associated with the part failures along with the repair actions used to fix the part failures. The best-practice knowledge is disseminated to the dealers involved in the anomaly cases. ASTEK has been implemented as a prototype in the service and quality department of GM and its performance has been validated in the real life set up. On an average, the analysis time is reduced from few weeks to few minutes, which in real life industry are significant improvements.

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Section: Part-based Clustersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A domain-specific decision support system for knowledge discovery using association and text mining

2011

Self Cite

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“…As mentioned in [20], "scheduling deals with the assignment of jobs and activities to resources and time ranges in accordance with relevant constraints and requirements." For a scientific workflow, its scheduling application is always promoted in a top-down way.…”

Section: Context Analyses Of Scientific Workflow Executionmentioning

confidence: 99%

“…To incorporate the soft real-time property into workflow scheduling application, a publicly accessible port should have some typical attributes of Has-Earliest-Start-Time, Has-Latest-Start-Time, Has-Earliest-End-Time, and Has-Latest-End-Time as specified in [20]. Moreover, a temporal-dependable service initiated by a publicly accessible port subscribes to Allen's [26] representation of standard time and relations between a private workflow fragment and a scientific workflow.…”

Section: Definitionmentioning

confidence: 99%

A collaborative scheduling approach for service-driven scientific workflow execution

Dou

Zhao

Fan

2010

Journal of Computer and System Sciences

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Scientific workflow execution often spans multiple self-managing administrative domains to obtain specific processing capabilities. Existing (global) analysis techniques tend to mandate every domain-specific application to unveil all private behaviors for scientific collaboration. In practice, it is infeasible for a domain-specific application to disclose its process details (as a private workflow fragment) for privacy or security reasons. Consequently, it is a challenging endeavor to coordinate scientific workflows and its distributed domain-specific applications. To address this problem, we propose a collaborative scheduling approach that can deal with temporal dependencies between a scientific workflow and a private workflow fragment. Under this collaborative scheduling approach, a private workflow fragment could maintain the temporal consistency with a scientific workflow in resource sharing and task enactments. Further, an evaluation is also presented to demonstrate the proposed approach for coordinating multiple scientific workflow executions in a concurrent environment.

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“…Our work made improvements on both the speed and depth of optimization, where multiple-day-spread was used to increase the search speed 1.29 times faster than single-day-shift, and configured search window was adopted to render better optimized search results. Generally speaking, our problem presents here is a class of resource allocation problem (RAP) [21], which searches for an optimal allocation of limited units of constrained resource to a number of activities for optimizing the objectives. The resource may be a person, an asset or capital which can be used to achieve a goal.…”

Section: Comparison With Related Workmentioning

confidence: 99%

Optimizing lead time and resource utilization for service enterprises

2008

SOCA

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Lead time is generally defined as the period of time for which customers have to wait before receiving completed products or services from enterprises. In the key public utility markets, such as telecommunications market, that are tightly regulated by government watchdogs, service enterprises are obliged to provide equivalent services to all their customers. In the context of service lead time, this means that "standard lead times" should be universally applied to all customers. Existing industrial practice in deriving "standard lead time" is manual and erroneous. Regardless of the variances of demand and resource across geographical areas and across time horizon, service enterprises are generally confined to single fixed "standard lead times". Ill-derived "standard lead times" lead to wrong promises made to customers, which not only forces service engineers to work overtime to deal with overflowing jobs but also incur huge compensation costs due to delayed or failed customer services. In this paper, we set out to tackle the "standard lead time" problem. In particular, we devised an automated approach to testing the existence of legal optimal allocation schemes based on actual customer demand, enterprise resource and assumed standard lead time. We first modelled this as a combinatorial optimisation problem; we then experimented a heuristic local search method, namely "single day shift", inspired by previous work on virtual telescope scheduling; further on, we improved the first method by introducing a new heuristics, namely "multiple day spread", which achieved a speed of search for optimal solutions, 1.29 times faster than the first method. A case study on comparisons between existing default "standard lead time" and the calculated one using our approach for a telecommunication service provider was conducted to demonstrate the necessity and effectiveness of this approach. Finally, we compared our approach with related work. We concluded that our approach is more suitable for the problem of optimizing lead time and resource utilisation, and the results from our work are widely applicable to various industry sectors that concern equivalent customer services, balanced work load and optimal lead times.

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A generic library of problem solving methods for scheduling applications

Cited by 10 publications

References 13 publications

A domain-specific decision support system for knowledge discovery using association and text mining

A domain-specific decision support system for knowledge discovery using association and text mining

A collaborative scheduling approach for service-driven scientific workflow execution

Optimizing lead time and resource utilization for service enterprises

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