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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Bat Algorithm, Genetic Algorithm and Shuffled Frog Leaping Algorithm for Designing Machine Layout
verfasst von : Kittipong Dapa, Pornpat Loreungthup, Srisatja Vitayasak, Pupong Pongcharoen
Erschienen in: Multi-disciplinary Trends in Artificial Intelligence
Verlag: Springer Berlin Heidelberg
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Arranging non-identical machines into a limited area of manufacturing shop floor is an essential part of plant design. Material handling distance is one of the key performance indexes of internal logistic activities within manufacturing companies. It leads to the efficient productivity and related costs. Machine layout design is known as facility layout problem and classified into non-deterministic polynomial-time hard problem. The objective of this paper was to compare the performance of Bat Algorithm (BA), Genetic Algorithm (GA) and Shuffled Frog Leaping Algorithm (SFLA) for designing machine layouts in a multiple-row environment with the aim to minimise the total material handling distance. An automated machine layout design tool has been coded in modular style using a general purpose programming language called Tcl/Tk. The computational experiment was designed and conducted using four MLD benchmark datasets adopted from literature. It was found that the proposed algorithms performed well in different aspects.