文章基本信息

标题：Good Parameters for PSO in Optimizing Laying Hen Diet
其他标题：Good Parameters for PSO in Optimizing Laying Hen Diet
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作者：Gusti Ahmad Fanshuri Alfarisy ; Wayan Firdaus Mahmudy ; Muhammad Halim Natsir 等
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2018
卷号：8
期号：4
页码：2419-2432
DOI：10.11591/ijece.v8i4.pp2419-2432
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Manual formulation of poultry diet by taking into account the fulfillment of all nutrients requirement with least cost is a difficult task. Particle Swarm Optimization (PSO) shows promising technique to solve this problem. However, there is a lack of studying a good parameter for PSO to solve feed formulation problem since PSO is sensitive to control parameter which depends on the problem. Therefore, this study investigates good swarm size, total iterations, acceleration coefficients, and inertia weight to produce a better formula. PSO with proposed good parameters is compared with other parameters. The obtained result shows that PSO with good parameters choice produces the highest fitness. Furthermore, good parameters of PSO can be used as a reference for a software developer and for further research to optimize poultry diet using PSO.
其他摘要：Manual formulation of poultry diet by taking into account the fulfillment of all nutrients requirement with least cost is a difficult task. Particle Swarm Optimization (PSO) shows promising technique to solve this problem. However, there is a lack of studying a good parameter for PSO to solve feed formulation problem since PSO is sensitive to control parameter which depends on the problem. Therefore, this study investigates good swarm size, total iterations, acceleration coefficients, and inertia weight to produce a better formula. PSO with proposed good parameters is compared with other parameters. The obtained result shows that PSO with good parameters choice produces the highest fitness. Furthermore, good parameters of PSO can be used as a reference for a software developer and for further research to optimize poultry diet using PSO.
关键词：Evolutionary Computation; Animal Diet Formulation;Feed Formulation Particle Swarm Optimization Good Parameter