Abstract
Nowadays, courier service has shown a tremendous increase in Malaysia. This courier service turned out to be progressively mainstream as the arrival of online shopping. Therefore, the courier service such as Skynet has a very wide potential to be the most successful business in Malaysia. However, courier service has a problem to specify the best route in order to optimize the time and distance hence save cost when doing a delivery. Most of the time not all the items can be sent within the specific time frame because the riders are lack of information in seeking how to determine the sequence of the road when doing a delivery. This problem is also known as the Travelling Salesman Problem (TSP). TSP can be solved by applying a Genetic Algorithm (GA). In this research, the distance travel from starting point into another point will determine the sequence of the road for the rider to do delivery. The data will be obtained from the actual event and the result will be compared. This Genetic Algorithm (GA) will determined the best and the shortest route from one point into another point that need to be taken by the riders. Therefore, by doing this research it can help the courier service company like Skynet to improve their service as well as to optimize the problem.
Metadata
Item Type: | Thesis (Degree) |
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Creators: | Creators Email / ID Num. Ahmad Nah Rodzi, Nah Izzattie Itqan 2016284418 |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Ibrahim, Khalipah UNSPECIFIED |
Subjects: | Q Science > Q Science (General) > Back propagation (Artificial intelligence) Q Science > QA Mathematics > Instruments and machines Q Science > QA Mathematics > Evolutionary programming (Computer science). Genetic algorithms |
Divisions: | Universiti Teknologi MARA, Terengganu > Kuala Terengganu Campus > Faculty of Computer and Mathematical Sciences |
Programme: | Bachelor of Science (Hons) Computational Mathematics |
Keywords: | Courier Service ; Travelling Salesman Problem ; Genetic Algorithm |
Date: | January 2020 |
URI: | https://ir.uitm.edu.my/id/eprint/39053 |
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