Abstract
The present work aims to develop a genetic algorithm (GA)-based approach to optimise the job-shop scheduling problem in a micro-brewery to minimise the production time and costs. In a production system, orders are placed randomly to form a queue. The problem is how to optimally schedule the tasks through the production process given the constraints on capacity and the customer satisfaction/service level. The work concentrates on formulating a mathematical model and to modify the scheduling problem based on a GA approach. © Springer International Publishing Switzerland 2015.
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CITATION STYLE
Shen, Z., Burnham, K. J., & Smalov, L. (2015). Optimised Job-Shop Scheduling via Genetic Algorithm for a Manufacturing Production System. In Advances in Intelligent Systems and Computing (Vol. 1089, pp. 89–92). Springer Verlag. https://doi.org/10.1007/978-3-319-08422-0_13
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