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Soft Computing

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04.12.2018 | Methodologies and Application

Product family flexibility design method based on hybrid adaptive ant colony algorithm

verfasst von: Wei Wei, Zhenyu Tian, Chong Peng, Ang Liu, Zhinan Zhang

Erschienen in: Soft Computing | Ausgabe 20/2019

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Abstract

This paper proposes a hybrid adaptive ant colony algorithm (HAACA) to realize product family multi-objective optimization design through scale-based product platform theory model. The Pareto-optimal solution was obtained via HAACA, and then the fuzzy optimization method is presented to extract the optimal solution of multi-objective optimization problem. The multi-objective optimization method was carried out in two stages. In the first stage, each product is optimized independently via HAACA and the product platform constant parameter and its value is obtained according to the change ratio of design variables. In the second stage, the scaling variables of each product are solved via HAACA based on the optimization objectives improving the performance in constraint of restrictions and the best compromise solution is extracted based on fuzzy optimization method.

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Titel: Product family flexibility design method based on hybrid adaptive ant colony algorithm
verfasst von: Wei Wei
Zhenyu Tian
Chong Peng
Ang Liu
Zhinan Zhang
Publikationsdatum: 04.12.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 20/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-018-3622-y

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