Putri, Anandistya Lisa and , Hari Prasetyo, ST, MT, Ph.D (2016) Perancangan Biased Random Key Genetic Algorithm dengan Multiple Populations untuk Menyelesaikan Capacitated Vehicle Routing Problem with Time Windows. Skripsi thesis, Universitas Muhammadiyah Surakarta.
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Abstract
This research deals with a variation of Vehicle Routing Problem (VRP) by accommodating capacity and time constraints, also known as Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). Soft drink distribution from depot to a number of outlets is an example of CTWVRP where every vehicle used to meet all demand from outlets must not exceed the capacity of the truck while the distribution process activity is restricted by the service hours at the distribution company. The main problem of this research is therefore how to determine the route of the truck such that the total transportation cost is minimized without violating the constraints. The CVRPTW is a Non Polynomial Hard (NP-Hard) Problem, therefore an efficient algorithm is needed to solve this problem effectively in a reasonable computation time. This research proposes a Biased Random Key Genetic Algorithm (BRKGA) with multiple populations which is coded in MATLAB for addressing the soft drink distribution. The performance of the proposed algorithm is then compared to a heuristic procedure that is previously used for dealing with the same problem. The result shows that the BRKGA with multiple population yields a lower total transportation cost compared to that of resulted from the heuristic. In addition, the use of multiple populations could further improve the performance of the basic BRKGA.
| Item Type: | Karya ilmiah (Skripsi) |
|---|---|
| Uncontrolled Keywords: | BRKGA, CVRPTW, genetic algorithms, multiple populations, vehicle routing problem |
| Subjects: | Q Science > Q Science (General) T Technology > T Technology (General) |
| Divisions: | Fakultas Teknik > Teknik Industri |
| Depositing User: | ANANDISTYA LISA PUTRI |
| Date Deposited: | 15 Aug 2016 04:42 |
| Last Modified: | 15 Aug 2016 04:42 |
| URI: | http://eprints.ums.ac.id/id/eprint/46045 |
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