SCOlog: A logic-based approach to analysing supply chain operation dynamics

Areti Manataki; Yun-Heh Chen-Burger; Michael Rovatsos

doi:10.1016/j.eswa.2013.07.008

SCOlog: A logic-based approach to analysing supply chain operation dynamics

Areti Manataki, Yun-Heh Chen-Burger, Michael Rovatsos

Research output: Contribution to journal › Article › peer-review

Abstract / Description of output

In a complex business world, characterised by globalisation and rapid rhythms of change, understanding supply chain (SC) operation dynamics is crucial. This paper describes a logic-based approach to analysing SC operation dynamics, named SCOlog. SC operation is modelled in a declarative fashion and it is simulated following rule-based execution semantics. This approach facilitates the automated explanation of simulated SC operational behaviours and performance. The automated explanation support provided by SCOlog is found to improve the understanding of the domain for non-SCM experts. Furthermore, SCOlog allows for maintainability and reusability.

Original language	English
Pages (from-to)	23-38
Number of pages	16
Journal	Expert Systems with Applications
Volume	41
Issue number	1
Early online date	15 Jul 2013
DOIs	https://doi.org/10.1016/j.eswa.2013.07.008
Publication status	Published - Jan 2014

Keywords / Materials (for Non-textual outputs)

Supply chain modelling
Supply chain simulation
Supply chain operation
Supply chain dynamics
Knowledge based system
Workflow
Business rules
Intelligent agent

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10.1016/j.eswa.2013.07.008

1-s2.0-S0957417413004855-main
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http://www.sciencedirect.com/science/article/pii/S0957417413004855

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title = "SCOlog: A logic-based approach to analysing supply chain operation dynamics",

abstract = "In a complex business world, characterised by globalisation and rapid rhythms of change, understanding supply chain (SC) operation dynamics is crucial. This paper describes a logic-based approach to analysing SC operation dynamics, named SCOlog. SC operation is modelled in a declarative fashion and it is simulated following rule-based execution semantics. This approach facilitates the automated explanation of simulated SC operational behaviours and performance. The automated explanation support provided by SCOlog is found to improve the understanding of the domain for non-SCM experts. Furthermore, SCOlog allows for maintainability and reusability.",

keywords = "Supply chain modelling , Supply chain simulation, Supply chain operation, Supply chain dynamics, Knowledge based system, Workflow, Business rules, Intelligent agent",

author = "Areti Manataki and Yun-Heh Chen-Burger and Michael Rovatsos",

year = "2014",

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language = "English",

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AU - Manataki, Areti

AU - Chen-Burger, Yun-Heh

AU - Rovatsos, Michael

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Y1 - 2014/1

N2 - In a complex business world, characterised by globalisation and rapid rhythms of change, understanding supply chain (SC) operation dynamics is crucial. This paper describes a logic-based approach to analysing SC operation dynamics, named SCOlog. SC operation is modelled in a declarative fashion and it is simulated following rule-based execution semantics. This approach facilitates the automated explanation of simulated SC operational behaviours and performance. The automated explanation support provided by SCOlog is found to improve the understanding of the domain for non-SCM experts. Furthermore, SCOlog allows for maintainability and reusability.

AB - In a complex business world, characterised by globalisation and rapid rhythms of change, understanding supply chain (SC) operation dynamics is crucial. This paper describes a logic-based approach to analysing SC operation dynamics, named SCOlog. SC operation is modelled in a declarative fashion and it is simulated following rule-based execution semantics. This approach facilitates the automated explanation of simulated SC operational behaviours and performance. The automated explanation support provided by SCOlog is found to improve the understanding of the domain for non-SCM experts. Furthermore, SCOlog allows for maintainability and reusability.

KW - Supply chain modelling

KW - Supply chain simulation

KW - Supply chain operation

KW - Supply chain dynamics

KW - Knowledge based system

KW - Workflow

KW - Business rules

KW - Intelligent agent

U2 - 10.1016/j.eswa.2013.07.008

DO - 10.1016/j.eswa.2013.07.008

M3 - Article

SN - 0957-4174

VL - 41

SP - 23

EP - 38

JO - Expert Systems with Applications

JF - Expert Systems with Applications

IS - 1

ER -

SCOlog: A logic-based approach to analysing supply chain operation dynamics

Abstract / Description of output

Keywords / Materials (for Non-textual outputs)

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