Salsabila, Hana (2025) Perbandingan Particle Swarm Optimization-Local Search dan Dynamic Evaporation Ant Colony Optimization dalam Perencanaan Rute Distribusi Barang. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Distribusi barang merupakan salah satu aspek penting dalam keberhasilan operasional perusahaan, terutama dalam menghadapi tantangan efisiensi dan efektivitas distribusi. Permasalahan routing yang kompleks, seperti Vehicle Routing Problem with Time Windows, membutuhkan pendekatan inovatif untuk mengoptimalkan rute distribusi. Pada beberapa studi yang telah dilakukan, menunjukkan efektivitas berbagai metode optimasi, seperti Dynamic Evaporation Ant Colony Optimization untuk Travelling Salesman Problem dan Particle Swarm Optimization-Local Search untuk efisiensi energi, namun dalam penelitian-penelitian tersebut belum ada yang berfokus untuk menyelesaikan masalah VRPTW. Berdasarkan hal tersebut, penelitian Tugas Akhir ini membandingkan metode PSO-LS dan DEACO untuk mengatasi permasalahan VRPTW, guna menentukan rute distribusi yang optimal dan efisien. Efektivitas metode terlihat berdasarkan total jarak tempuh dari rute yang terbentuk. Hasil dari penelitian Tugas Akhir ini menunjukkan bahwa metode DEACO lebih efektif dibandingkan metode PSO-LS untuk menyelesaikan permasalahan VRPTW. Hal itu terlihat dari hasil total jarak tempuh rute dari metode DEACO adalah 297,4 km untuk 2 kendaraan yang beroperasi, sedangkan metode PSO-LS menghasilkan total jarak tempuh rute adalah 334,8 km. Berdasarkan hasil perhitungan dan komputasi yang telah dilakukan, ditemukan bahwa metode DEACO dapat secara signifikan membantu dalam menentukan rute distribusi barang
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Distribution of goods is one of the important aspects in the success of a company's operations, especially in facing the challenges of distribution efficiency and effectiveness. Complex routing problems, such as the Vehicle Routing Problem with Time Windows, require an innovative approach to optimize distribution routes. Several studies have shown the effectiveness of various optimization methods, such as Dynamic Evaporation Ant Colony Optimization for the Traveling Salesman Problem and Particle Swarm Optimization-Local Search for energy efficiency, but none of these studies have focused on solving the VRPTW problem. Based on this, this Final Project study compares the PSO-LS and DEACO methods to solve the VRPTW problem, in order to determine the optimal and efficient distribution route. The effectiveness of the method is seen based on the total distance traveled by the route formed. The results of this Final Project study show that the DEACO method is more effective than the PSO-LS method in solving the VRPTW problem. This can be seen from the results of the total route distance traveled by the DEACO method which is 297.4 km for 2 operating vehicles, while the PSO-LS method produces a total route distance of 334.8 km. Based on the results of the calculations and computations that have been carried out, it was found that the DEACO method can significantly help in determining the distribution route of goods.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Distribusi, Dynamic Evaporation Ant Colony Optimization, Particle Swarm Optimization, Local Search, Vehicle Routing Problem with Time Windows Distribution, Dynamic Evaporation Ant Colony Optimization, Particle Swarm Optimization, Local Search, Vehicle Routing Problem with Time Windows |
| Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD38.5 Business logistics--Cost effectiveness. Supply chain management. ERP Q Science > Q Science (General) > Q337.3 Swarm intelligence Q Science > QA Mathematics > QA166 Graph theory |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis |
| Depositing User: | Hana Salsabila |
| Date Deposited: | 02 Feb 2025 04:27 |
| Last Modified: | 02 Feb 2025 04:27 |
| URI: | http://repository.its.ac.id/id/eprint/116910 |
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