Engineering optimization problems
This project aims to solve engineering optimization problems using the differential evolution method. In this report, overview, and general procedures on the Differential Evolution is discussed and various constraint handling methods were discussed. The optimization codes were written in python.
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Nanyang Technological University
2020
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sg-ntu-dr.10356-1368772023-07-07T18:02:08Z Engineering optimization problems Ramakrishnan Sivasankar Ponnuthurai N. Suganthan School of Electrical and Electronic Engineering epnsugan@ntu.edu.sg Engineering::Electrical and electronic engineering Science::Mathematics::Applied mathematics::Optimization This project aims to solve engineering optimization problems using the differential evolution method. In this report, overview, and general procedures on the Differential Evolution is discussed and various constraint handling methods were discussed. The optimization codes were written in python. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-02-04T06:56:13Z 2020-02-04T06:56:13Z 2019 Final Year Project (FYP) https://hdl.handle.net/10356/136877 en application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Science::Mathematics::Applied mathematics::Optimization Ramakrishnan Sivasankar Engineering optimization problems |
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This project aims to solve engineering optimization problems using the differential evolution method. In this report, overview, and general procedures on the Differential Evolution is discussed and various constraint handling methods were discussed. The optimization codes were written in python. |
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Ponnuthurai N. Suganthan |
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Ponnuthurai N. Suganthan Ramakrishnan Sivasankar |
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Final Year Project |
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Ramakrishnan Sivasankar |
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Ramakrishnan Sivasankar |
title |
Engineering optimization problems |
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Engineering optimization problems |
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Engineering optimization problems |
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Engineering optimization problems |
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Engineering optimization problems |
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engineering optimization problems |
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Nanyang Technological University |
publishDate |
2020 |
url |
https://hdl.handle.net/10356/136877 |
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