| 書(shū)目名稱 | Nature-Inspired Optimization Algorithms with Java |
| 副標(biāo)題 | A Look at Optimizati |
| 編輯 | Shashank Jain |
| 視頻video | http://file.papertrans.cn/663/662079/662079.mp4 |
| 概述 | Easy to understand code examples of nature inspired algorithms.Covers most of the optimization solutions by nature inspired algorithms.Covers applications of each of the algorithms in specific industr |
| 圖書(shū)封面 |  |
| 描述 | Gain insight into the world of nature-inspired optimization techniques and algorithms. This book will prepare you to apply different nature-inspired optimization techniques to solve problems using Java..You‘ll start with an introduction to the hidden algorithms that nature uses and find the approximate solutions to optimization problems. You‘ll then see how living creatures such as fish and birds are able to perform computation to solve specific optimization tasks. This book also covers various nature-inspired algorithms by reviewing code examples for each one followed by crisp and clear explanations of the algorithm using Java code. You‘ll examine the use of each algorithm in specific industry scenarios?such as fleet scheduling in supply chain management, and shop floor management in industrial and manufacturing applications.?.Nature-Inspired Optimization Algorithms with Java. is your pathway to understanding a variety of optimization problems that exist in various industries and domains and it will develop an ability to apply nature-inspired algorithms to find approximate solutions to them..What You‘ll Learn.Study optimization and its problems.Examine nature-inspired algorithms s |
| 出版日期 | Book 2022 |
| 關(guān)鍵詞 | Python; Algorithm; Optimization; Swarm Intelligence; Complex Systems; Ant colony optimization; Whale optim |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4842-7401-9 |
| isbn_softcover | 978-1-4842-7400-2 |
| isbn_ebook | 978-1-4842-7401-9 |
| copyright | Shashank Jain 2022 |
|Archiver|手機(jī)版|小黑屋|
派博傳思國(guó)際
( 京公網(wǎng)安備110108008328)
GMT+8, 2025-10-11 12:31
發(fā)表于 2025-3-21 17:44:34
