A multi-agent based system for e-procurement exception management

Liu, Quan; Sun, Sherry; Wang, Huaiqing; Zhao, Jing

doi:10.1016/j.knosys.2010.07.004

Cited by 24 publications

(38 citation statements)

References 38 publications

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“…Pinson et al [18] describe a blackboard-based architecture [19], a task decomposition of the SP process into a number of modules (agents) with different knowledge levels and goals and a mechanism to enable the cooperation and negotiation among these agents. Liu et al [20] show the flexibility of MAS to deal with internal/external environment uncertainty and its knowledge and to handle planning changes.…”

Section: Intelligent Organizationsmentioning

confidence: 99%

Leveraging information for high level-of-abstraction organizational processes

Dalmau-Espert¹,

Largo²,

Compañ³

et al. 2016

Int. J. DNE

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Nowadays, Big Data techniques have made possible to obtain interesting low-level information from large amounts of data. However, the information is often difficult to be enriched enough to aid in high-level organizational processes. The objective of this work is to define a model to allow the use of available information for the design and implementation of high level-of-abstraction processes that take place in the organizations. Particularly, this paper is focused on the strategic planning (SP) process, one of the most complex and abstract processes in any company. So far, there are very few successful attempts to automate this process, which is usually based on manual tasks. At the most, the results from the automatic data analysis are generated and used as reports and are not integrated in the process. A further step is proposed, posing a SP model based on a multi-agent system with a blackboard, which is used as a means of communication and storage of the generated information. The information is described using ontology to formalize both the SP process and the information used in each step. The combination of these elements enables the participation, interaction and sharing of information and knowledge of the participants in the process. The accumulated knowledge allows the use of previous experience to automate the process and improve the decision making. In short, the proposed model is a formal, comprehensive, agile and flexible solution to perform the process of SP in organizations today leveraging of the enormous amount of available data and the gathered experience.

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Section: Intelligent Organizationsmentioning

confidence: 99%

Leveraging information for high level-of-abstraction organizational processes

Dalmau-Espert¹,

Largo²,

Compañ³

et al. 2016

Int. J. DNE

View full text Add to dashboard Cite

show abstract

“…Since its development KBS has been widely applied to various studies and issues, including performance assessment [57,59,56], e-procurement exception management [36], stock market investment [9], product pricing [48], dynamic logistics process management [11], marketing decision [61], outsource manufacturing [10], urban infrastructure management [45], cost estimating [40], bank loan risk management [60], airborne decision support [23], strategic planning [24], work-related risk analysis [43], debris-flow problems analysis [55], and production [44]. Consequently, the KBS has gained considerable acceptance recently in the current information management literature.…”

Section: The Components Of Knowledge-based System and Related Applicamentioning

confidence: 99%

Designing a knowledge-based system for benchmarking: A DEA approach

Lai

Huang

Wang

2011

Knowledge-Based Systems

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“…Research in dependence on suppliers carried out for example in [5][6][7]. Let's fix the node-enterprise ܲ we are interested in and the external stability factor that we would like to calculate.…”

Section: Introductionmentioning

confidence: 99%