Browse DORAS
Browse Theses
Search
Latest Additions
Creative Commons License
Except where otherwise noted, content on this site is licensed for use under a:

Performance optimization of a leagility inspired supply chain model: a CFGTSA algorithm based approach

Chan, Felix T.S. and Kumar, Vikas (2009) Performance optimization of a leagility inspired supply chain model: a CFGTSA algorithm based approach. International Journal of Production Research, 47 (3). pp. 777-799. ISSN 1366-588X

Full text available as:

[img]Microsoft Word
425Kb
[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
687Kb

Abstract

Lean and agile principles have attracted considerable interest in the past few decades. Industrial sectors throughout the world are upgrading to these principles to enhance their performance, since they have been proven to be efficient in handling supply chains. However, the present market trend demands a more robust strategy incorporating the salient features of both lean and agile principles. Inspired by these, the leagility principle has emerged, encapsulating both lean and agile features. The present work proposes a leagile supply chain based model for manufacturing industries. The paper emphasizes the various aspects of leagile supply chain modeling and implementation and proposes a new Hybrid Chaos-based Fast Genetic Tabu Simulated Annealing (CFGTSA) algorithm to solve the complex scheduling problem prevailing in the leagile environment. The proposed CFGTSA algorithm is compared with the GA, SA, TS and Hybrid Tabu SA algorithms to demonstrate its efficacy in handling complex scheduling problems.

Item Type:Article (Published)
Refereed:Yes
Subjects:Engineering > Production engineering
Computer Science > Artificial intelligence
Computer Science > Algorithms
DCU Faculties and Centres:DCU Faculties and Schools > DCU Business School
Publisher:Taylor and Francis
Official URL:http://dx.doi.org/10.1080/00207540600844068
Copyright Information:Copyright 2009 Taylor & Francis
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:15771
Deposited On:02 Nov 2010 11:17 by Dr Vikas Kumar. Last Modified 02 Nov 2010 11:21

Download statistics

Archive Staff Only: edit this record