Article ID: | iaor20105702 |
Volume: | 7 |
Issue: | 2 |
Start Page Number: | 215 |
End Page Number: | 230 |
Publication Date: | Aug 2010 |
Journal: | International Journal of Services and Operations Management |
Authors: | Amuthakkannan R, Babu C K, Kannan S M |
Keywords: | scheduling, heuristics: ant systems |
In modern industries, the optimisation of processes is very important to increase productivity. There are many optimisation techniques applied in the various processes of industries. In textile mills, cotton passes through a series of processes like carding, drawing, combing, etc. As various grades of cotton are processed in machines, the textile industry involves complex processes. Owing to this complexity, there is always a need for better optimisation techniques to reduce the makespan to increase productivity. Ant Colony Optimisation (ACO) is one of the most important optimisation techniques and is widely used in the process industry. This work overviews the application of ACO to minimise makespan in a textile industry by sequencing 'n' jobs of a spinning process in 'm' machines. A real-time problem from a textile industry has been analysed and the best optimal sequences for scheduling jobs have been found using ACO. In the first part of the paper, the need for a better optimisation technique in a textile industry is overviewed, along with some basic biological findings on real ants. In the second part, an algorithm for optimisation is derived, data collected from a textile industry are used to implement the algorithm and the sequencing of jobs in machines is identified. The obtained result depicts the need of ACO for makespan reduction in a textile industry.