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The relevance of outsourcing and leagile strategies in performance optimization of an integrated process planning and scheduling

Chan, Felix T.S. and Kumar, Vikas and Tiwari, Manoj Kumar (2009) The relevance of outsourcing and leagile strategies in performance optimization of an integrated process planning and scheduling. International Journal of Production Research, 47 (1). pp. 119-142. ISSN 1366-588X

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Abstract

Over the past few years growing global competition has forced the manufacturing industries to upgrade their old production strategies with the modern day approaches. As a result, recent interest has been developed towards finding an appropriate policy that could enable them to compete with others, and facilitate them to emerge as a market winner. Keeping in mind the abovementioned facts, in this paper the authors have proposed an integrated process planning and scheduling model inheriting the salient features of outsourcing, and leagile principles to compete in the existing market scenario. The paper also proposes a model based on leagile principles, where the integrated planning management has been practiced. In the present work a scheduling problem has been considered and overall minimization of makespan has been aimed. The paper shows the relevance of both the strategies in performance enhancement of the industries, in terms of their reduced makespan. The authors have also proposed a new hybrid Enhanced Swift Converging Simulated Annealing (ESCSA) algorithm, to solve the complex real-time scheduling problems. The proposed algorithm inherits the prominent features of the Genetic Algorithm (GA), Simulated Annealing (SA), and the Fuzzy Logic Controller (FLC). The ESCSA algorithm reduces the makespan significantly in less computational time and number of iterations. The efficacy of the proposed algorithm has been shown by comparing the results with GA, SA, Tabu, and hybrid Tabu-SA optimization methods.

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/10.1080/00207540600818195
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:15772
Deposited On:02 Nov 2010 10:02 by Dr Vikas Kumar. Last Modified 02 Nov 2010 10:02

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