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Titlebook: Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach; Duc Truong Pham,Natalia Hartono Book 2023 The Editor(s)

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发表于 2025-3-21 19:02:17 | 显示全部楼层 |阅读模式
书目名称Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach
编辑Duc Truong Pham,Natalia Hartono
视频videohttp://file.papertrans.cn/470/469877/469877.mp4
概述Explains the bees algorithm a highly effective optimization algorithm.Presents the application of the Bees Algorithm to solve a wide range of complex problems.Covers new topics such as smart optimisat
丛书名称Springer Series in Advanced Manufacturing
图书封面Titlebook: Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach;  Duc Truong Pham,Natalia Hartono Book 2023 The Editor(s)
描述.This book is the first work dedicated to the Bees Algorithm. Following a gentle introduction to the main ideas underpinning the algorithm, the book presents recent results and developments relating to the algorithm and its application to optimisation problems in production and manufacturing... ..With the advent of the Fourth Industrial Revolution, production and manufacturing processes and systems have become more complex. To obtain the best performance from them requires efficient and effective optimisation techniques that do not depend on the availability of process or system models. Such models are usually either not obtainable or mathematically intractable due to the high degrees of nonlinearities and uncertainties in the processes and systems to be represented. The Bees Algorithm is a powerful swarm-based intelligent optimisation metaheuristic inspired by the foraging behaviour of honeybees. The algorithm is conceptually elegant and extremely easy to apply. All it needs to solve an optimisation problem is a means to evaluate the quality of potential solutions.. ..This book demonstrates the simplicity, effectiveness and versatility of the algorithm and encourages its further a
出版日期Book 2023
关键词Intelligent Manufacturing; Smart Manufacturing; Intelligent Optimisation; Swarm Intelligence; Bees Algor
版次1
doihttps://doi.org/10.1007/978-3-031-14537-7
isbn_softcover978-3-031-14539-1
isbn_ebook978-3-031-14537-7Series ISSN 1860-5168 Series E-ISSN 2196-1735
issn_series 1860-5168
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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https://doi.org/10.1007/978-3-031-14537-7Intelligent Manufacturing; Smart Manufacturing; Intelligent Optimisation; Swarm Intelligence; Bees Algor
发表于 2025-3-22 05:10:21 | 显示全部楼层
978-3-031-14539-1The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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发表于 2025-3-22 16:51:12 | 显示全部楼层
1860-5168 f complex problems.Covers new topics such as smart optimisat.This book is the first work dedicated to the Bees Algorithm. Following a gentle introduction to the main ideas underpinning the algorithm, the book presents recent results and developments relating to the algorithm and its application to o
发表于 2025-3-22 17:50:53 | 显示全部楼层
Minimising Printed Circuit Board Assembly Time Using the Bees Algorithm with TRIZ-Inspired Operatorson a PCB assembly with 50 component locations with improved results in each case study. This research explores how the Bees Algorithm with TRIZ-inspired operators is applied to this case study to reduce the assembly time to 23.42 s to save significant cost and time when compared to other past research work with different optimisation algorithms.
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发表于 2025-3-23 04:11:14 | 显示全部楼层
A Case Study with the BEE-Miner Algorithm: Defects on the Production Linegorithms are used to classify the defects in the production line of a textile company in a considerably better way. When results on the quality defect dataset are analysed, it is observed that BEE-miner algorithm outperforms the MEPAR-miner algorithm in terms of classification cost and accuracy.
发表于 2025-3-23 06:43:46 | 显示全部楼层
Shape Recognition for Industrial Robot Manipulation with the Bees Algorithm Algorithm is evaluated on three sets of artificial scenes of varying degrees of blurriness and benchmarked against an evolutionary algorithm. Experimental results proved the precision and consistency of the Bees Algorithm. Primitive fitting times were compatible with real-time application.
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