Nitesh Khilwani
Tool Selection in FMS A Hybrid SA-Tabu Algorithm Based Approach
Khilwani, Nitesh; Harding, J. A.; Mishra, Nishikant
Authors
J. A. Harding
Professor Nishikant Mishra Nishikant.Mishra@hull.ac.uk
Professor/ Head of Management Systems Subject Group
Contributors
Manoj Tiwari
Editor
Jenny A. Harding
Editor
Abstract
A major advantage of Flexible Manufacturing Systems (FMS) is that a family of related parts can be processed simultaneously using sets of computer controlled workstations, capable of performing a number of different operations and interconnected by automated material handling devices. Flexible manufacturing industry is marked by the coexistence of several resources with varying capabilities, capacities and functions. In such systems the selection of appropriate resources (e.g. tool selection, tool management or tool loading) for machines and allocation of appropriate resources to them is one of the major decision problems. This problem is generally handled by two approaches, i.e. by minimizing the total manufacturing cost or by minimizing the total manufacturing time. Both these approaches lead to NP-hard problems and thus need the application of heuristic techniques or AI based optimization tools to achieve an optimal or near optimal solution. In this chapter, a hybrid algorithm named Simulated Annealing-Tabu is utilized to solve this computationally complex problem. This hybrid algorithm exploits the features of tabu search and simulated annealing to ensure convergence at a faster rate. © 2011 Scrivener Publishing LLC. All rights reserved.
Citation
Khilwani, N., Harding, J. A., & Mishra, N. (2011). Tool Selection in FMS A Hybrid SA-Tabu Algorithm Based Approach. In M. Tiwari, & J. A. Harding (Eds.), Evolutionary Computing in Advanced Manufacturing (123-150). Wiley. https://doi.org/10.1002/9781118161883.ch7
Publication Date | Aug 22, 2011 |
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Deposit Date | Jun 8, 2022 |
Publisher | Wiley |
Pages | 123-150 |
Book Title | Evolutionary Computing in Advanced Manufacturing |
Chapter Number | 7 |
ISBN | 9780470639245 |
DOI | https://doi.org/10.1002/9781118161883.ch7 |
Public URL | https://hull-repository.worktribe.com/output/3614017 |
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