Optimization algorithms with adaptive learning for logistic planning
With the rise in popularity of Artificial Intelligence (AI) over the years, it has become more important than ever to capitalise on this interest to not only educate those who are interested, but also to inspire them to develop this interest into a skill. However, without knowledge of coding, it is...
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Nanyang Technological University
2020
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sg-ntu-dr.10356-1452332023-07-07T18:10:30Z Optimization algorithms with adaptive learning for logistic planning Lee, Yan Hui Meng-Hiot Lim School of Electrical and Electronic Engineering EMHLIM@ntu.edu.sg Engineering::Electrical and electronic engineering::Computer hardware, software and systems With the rise in popularity of Artificial Intelligence (AI) over the years, it has become more important than ever to capitalise on this interest to not only educate those who are interested, but also to inspire them to develop this interest into a skill. However, without knowledge of coding, it is difficult for people to learn about AI effectively. This project aims to address this issue by aiming to solve a popular computational problem called the Traveling Salesman Problem (TSP), which is an abstract representation of general logistic planning issues. By introducing a holistic package, which includes building hardware (Arduino based, wirelessly-controlled vehicle) and coding software for beginners, and by choosing materials which are easily available and accessible, both online and offline, it ensures that the barrier to entry is kept low to maximise the interest of learners. At the end of the program, learners would get to demonstrate their knowledge by showcasing their vehicle and code to solve a logistic planning scenario. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-12-15T07:06:01Z 2020-12-15T07:06:01Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/145233 en A2324-192 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering::Computer hardware, software and systems Lee, Yan Hui Optimization algorithms with adaptive learning for logistic planning |
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With the rise in popularity of Artificial Intelligence (AI) over the years, it has become more important than ever to capitalise on this interest to not only educate those who are interested, but also to inspire them to develop this interest into a skill. However, without knowledge of coding, it is difficult for people to learn about AI effectively. This project aims to address this issue by aiming to solve a popular computational problem called the Traveling Salesman Problem (TSP), which is an abstract representation of general logistic planning issues. By introducing a holistic package, which includes building hardware (Arduino based, wirelessly-controlled vehicle) and coding software for beginners, and by choosing materials which are easily available and accessible, both online and offline, it ensures that the barrier to entry is kept low to maximise the interest of learners. At the end of the program, learners would get to demonstrate their knowledge by showcasing their
vehicle and code to solve a logistic planning scenario. |
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Meng-Hiot Lim |
author_facet |
Meng-Hiot Lim Lee, Yan Hui |
format |
Final Year Project |
author |
Lee, Yan Hui |
author_sort |
Lee, Yan Hui |
title |
Optimization algorithms with adaptive learning for logistic planning |
title_short |
Optimization algorithms with adaptive learning for logistic planning |
title_full |
Optimization algorithms with adaptive learning for logistic planning |
title_fullStr |
Optimization algorithms with adaptive learning for logistic planning |
title_full_unstemmed |
Optimization algorithms with adaptive learning for logistic planning |
title_sort |
optimization algorithms with adaptive learning for logistic planning |
publisher |
Nanyang Technological University |
publishDate |
2020 |
url |
https://hdl.handle.net/10356/145233 |
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1772825880588976128 |