A Genetic Algorithm and Fuzzy Logic-based approach for measuring performance in a supply chain management

Djennas Mustapha; Benhabib Abderrezzak

Article Details

A Genetic Algorithm and Fuzzy Logic-based approach for measuring performance in a supply chain management

Authors:

Djennas Mustapha | Benhabib Abderrezzak

Publisher:

Université Aboubeker Belkaid de Tlemcen

Journal:

les cahiers du mecas Vol.5 Issue 1, pp.11-25

Document Type:

Article

Publication Date:

12/2009

Document Language:

English

Document ID (Org No.):

2001406436

pISSN:

2600-6294

Keywords:

Abstract:

 In today’s global market, reaching a competitive advantage by integrating firms in a supply chain management strategy becomes a key success for any firm seeking to survive in a complex environment. However, as interactions between agents in the supply chain management (SCM) remain unpredictable, simulation appears as a powerful tool aiming at predicting market behavior and agents’ performance levels. This paper discusses the issues of supply chain management and the requirements for supply chain simulation modeling. It reviews the relationships between Artificial Intelligence (AI) and SCM and concludes that under some conditions, SCM models exhibit some inadequacies that may be enriched by the use of AI tools. This approach aims at testing the supply chain activities of nine companies in the crude oil market. The objective is to tackle the issues under which agents can coexist in a competitive environment. Furthermore, we will specify the supply chain management trading interaction between agents by using an optimization approach based on a Genetic Algorithm (AG), Clustering and Fuzzy Logic (FL).
Results support the view that the structured model provides a good tool for modeling the supply chain activities using AI methodology.

Article Details

A Genetic Algorithm and Fuzzy Logic-based approach for measuring performance in a supply chain management

Authors:

Djennas Mustapha | Benhabib Abderrezzak

Publisher:

Université Aboubeker Belkaid de Tlemcen

Journal:

les cahiers du mecas Vol.5 Issue 1, pp.11-25

Document Type:

Article

Publication Date:

12/2009

Document Language:

English

Document ID (Org No.):

2001406436

pISSN:

2600-6294

Supply chain management

genetic algorithm

fuzzy logic

clustering

optimization

Issues

Article Details

A Genetic Algorithm and Fuzzy Logic-based approach for measuring performance in a supply chain management

Authors: Djennas Mustapha | Benhabib Abderrezzak

Publisher: Université Aboubeker Belkaid de Tlemcen

Journal: les cahiers du mecas Vol.5 Issue 1, pp.11-25

Document Type: Article

Publication Date: 12/2009

Document Language: English

Document ID (Org No.): 2001406436

pISSN: 2600-6294

Supply chain management

genetic algorithm

fuzzy logic

clustering

optimization

Issues

Authors:

Djennas Mustapha | Benhabib Abderrezzak

Publisher:

Université Aboubeker Belkaid de Tlemcen

Journal:

les cahiers du mecas Vol.5 Issue 1, pp.11-25

Document Type:

Article

Publication Date:

12/2009

Document Language:

English

Document ID (Org No.):

2001406436

pISSN:

2600-6294