Abstract
Vehicle Routing Problem (VRP) is a combinatorial optimization that consists of finding an optimal object from a finite set of objects. The objective of the VRP is to find a series of routes at a minimal cost which means by finding the shortest direction, minimizing the number of vehicles and others from the beginning and ending the route at the depot, so that the known demands of all nodes are fully occupied. We are using four step in methodology as determine of genetic algorithm characteristic, data input, the process by using operator selection and prediction. the results have been compares with two operator selection to determine the minimum routes in cities. Based on the study that have been conducted the minimum routes is equal to 3990. The selected order route is 1-2-3-4-5-6-7- 8-9-10-ll-12-13-14-15-18-19-16-17-20-21- 22-25-24-23. From the results of the studies that have been conducted, it can be concluded that GA method can be used in the routes of large city. But it is not the best method, in other words, we can't guarantee whether the table this is the best solution. Therefore, the solution obtained is regarded as approximations only. Normally this GA to obtain a solution that is almost the best solution quickly and easily. Therefore, a more thorough study could be done to improve the methods that have been discussed, in particular the GA method by setting conditions for the processes in the GA.
Metadata
Item Type: | Student Project |
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Creators: | Creators Email / ID Num. Jamaluddin, Mohammad Izwan 2014829388 Mohd Shukri, Muhamad Syahmie Adeeb 2014407422 |
Contributors: | Contribution Name Email / ID Num. Advisor Ifwah, Wan Nurfahizul UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Probabilities Q Science > QA Mathematics > Sequences (Mathematics) Q Science > QA Mathematics > Analysis |
Divisions: | Universiti Teknologi MARA, Kelantan > Machang Campus > Faculty of Computer and Mathematical Sciences |
Programme: | Mathematics Project (MAT660) |
Keywords: | Vehicle Routing Problem (VRP), genetic algorithm (GA), routes, selected order, genetic algorithm characteristic |
Date: | 2016 |
URI: | https://ir.uitm.edu.my/id/eprint/109321 |
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