Globalisation and the advent in manufacturing technology have resulted in a more turbulent and rapidly changing market, where more and more unpredictable factors influence market opportunities. In order to maintain a steady share of the market and to survive in a competitive environment, it is necessary to respond rapidly to changes. Agile manufacturing is a manufacturing paradigm developed to meet the challenges which stem from an unpredictable global market. This work attempts to explore the possibility of solving an assembly line balancing problem using a novel tabu-enhanced genetic algorithm approach. An attempt is made to compare the qualities of the optimised solutions produced by genetic algorithms and tabu search. A case study on a tower computer assembly was used to validate the proposed approach. The details of the approach as well as a case study are presented.
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ID="A1" Correspondence and offprint requests to: Dr L. P. Khoo, School of Mechanical and Production Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798. E-mail: mlpkhoo@ntu.edu.sg
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Khoo, L., Loi, M. A Tabu-Enhanced Genetic Algorithm Approach to Agile Manufacturing. Int J Adv Manuf Technol 20, 692–700 (2002). https://doi.org/10.1007/s001700200208
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DOI: https://doi.org/10.1007/s001700200208