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Proceedings ArticleDOI

Using rough sets for optimal cost evaluation in supply chain management

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TLDR
This paper analyzed and demonstrated a method for optimal cost evaluation using the rough set theory and targeted on finding the qualitative causal relationships that exist between various businesses and their associated attributes.
Abstract
Over the last decade we have seen rapid advancement in the field of rough set theory. It has been successfully been applied to many varied fields such as data mining and network intrusion detection with little or no modifications. The concept of rough set is increasingly becoming popular which can be easily seen from the increasing number of research articles devoted to it. In the past several studies have targeted on finding the qualitative causal relationships that exist between various businesses and their associated attributes. This has resulted in the need for a quantitative approach for the evaluation of cost for supply chain management. However since the process for supply chain management itself depends on multiple complicated features regarding which the standard statistical techniques are not deemed suitable. Therefore in this paper we have analyzed and demonstrated a method for optimal cost evaluation using the rough set theory.

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Citations
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Book ChapterDOI

Trend of energy consumption in developing nations in the last two decades: a case study from a statistical perspective

TL;DR: In this paper, the authors provided an overview of the trends in consumption of energy and its source: renewable and non-renewable across the globe with a focus on the developing nations.
Proceedings ArticleDOI

A novel hybrid model for network intrusion detection

TL;DR: This paper presents an intrusion detection scheme using Neural Networks, Rough sets and Firefly Algorithm (FA) to find and establish appropriate defenses against any malicious attack on the network.
Proceedings ArticleDOI

Study of Supply Chain Coordination Contract Model based on Rough Set and Markov Chain

Hailan Ran
TL;DR: The Markov Chain is trained using the extended Rough Set of hidden layer information to simplify the basic indicator data, and an improved method based on index training information reduction and Rough Set training is constructed by superimposing different time series.
References
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Journal ArticleDOI

Defining supply chain management

TL;DR: A management construct cannot be used effectively by practitioners and researchers if a common agreement on its definition is lacking as discussed by the authors, which is the case with the term "supply chain management".
Journal ArticleDOI

The Supply Chain Management Processes

TL;DR: In this paper, the authors provide strategic and operational descriptions of each of the eight supply chain processes identified by members of The Global Supply Chain Forum, as well as illustrations of the interfaces among the processes and an example of how a process approach can be implemented within an organization.
Journal ArticleDOI

A strategic model for supply chain design with logical constraints: formulation and solution

TL;DR: This paper proposes a strategic production-distribution model for supply chain design with consideration of bills of materials, and shows how these relationships are formulated as logical constraints in a mixed integer programming (MIP) model, thus capturing the role of BOM in the selection of suppliers in the strategic design of a supply chain.
Journal ArticleDOI

Achieving High Satisfaction in Supplier-Dealer Relationships

TL;DR: In this paper, a conceptual model including behavioral dimensions of supplier-dealer relationships and hypotheses about how to achieve satisfactory inter-organizational relationships is proposed, and the model is an empirical assessment of the relationship between Swedish lumber dealers and their suppliers.
Journal ArticleDOI

Rough sets bankruptcy prediction models versus auditor signalling rates

TL;DR: The rough sets models developed in this research did not provide any significant comparative advantage with regard to prediction accuracy over the actual auditors' methodologies, and should be fairly robust.
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