Abstract
This paper examines a cellular manufacturing optimisation problem in a new facility of a pharmaceutical company. The new facility, together with the old one, should be adequate to handle current and future production requirements. The aim of this paper is to investigate the potential use of evolutionary computation in order to find the optimum configuration of the cells in the facility. The objective is to maximise the total number of batches processed per year in the facility. In addition, a two-objective optimisation search was implemented, using several evolutionary computation methods. One additional objective is to minimise the overall cost, which is proportional to the number of cells in the facility. The multi-objective optimisation programs were based on three approaches: The weighted-sum approach, the Pareto-optimality approach, and the Multiobjective Genetic Algorithm (MOGA) approach.
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© 1998 Springer-Verlag London Limited
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Dimopoulos, C., Zalzala, A.M.S. (1998). Evolutionary Computation Approaches to Cell Optimisation. In: Parmee, I.C. (eds) Adaptive Computing in Design and Manufacture. Springer, London. https://doi.org/10.1007/978-1-4471-1589-2_6
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DOI: https://doi.org/10.1007/978-1-4471-1589-2_6
Publisher Name: Springer, London
Print ISBN: 978-3-540-76254-6
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