Optimization of Pertamax Fuel Distribution Using Clarke-Wright Savings, Nearest Neighbour, and Goal Programming (Case Study: Malang City)
Fuel distribution optimization is crucial to meet growing demand and reduce operational costs, especially in cities like Malang, where vehicle numbers are increasing. This research addresses the distribution challenges of PT Pertamina, focusing on designing efficient routes to minimize distance, cos...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Mathematics Department UIN Maulana Malik Ibrahim Malang
2025-03-01
|
| Series: | Cauchy: Jurnal Matematika Murni dan Aplikasi |
| Subjects: | |
| Online Access: | https://ejournal.uin-malang.ac.id/index.php/Math/article/view/31529 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850195401344286720 |
|---|---|
| author | Tharisa Melani Sobri Abusini Marjono Marjono |
| author_facet | Tharisa Melani Sobri Abusini Marjono Marjono |
| author_sort | Tharisa Melani |
| collection | DOAJ |
| description | Fuel distribution optimization is crucial to meet growing demand and reduce operational costs, especially in cities like Malang, where vehicle numbers are increasing. This research addresses the distribution challenges of PT Pertamina, focusing on designing efficient routes to minimize distance, cost, and delivery time while meeting fuel demands effectively. The problem, classified as a Capacitated Vehicle Routing Problem (CVRP), is solved using the Clarke-Wright Savings (CWS), Nearest Neighbour (NN), and Goal Programming (GP). The CWS is applied to group routes efficiently by reducing travel distances, while NN determined the delivery sequence within each route. GP addressed multi-objective optimization, minimizing costs and delivery time, maximizing Pertashop demands, and optimizing vehicle use. The results show that the combination of CWS and NN algorithms reduced the total travel distance by 140 km, or 12.5% reduction. Additionally, the GP method optimized vehicle use to 13, achieving a 59.68% cost reduction and a 48.68% time savings. These findings highlight the effectiveness of combining these algorithms in fuel distribution optimization, providing a more efficient solution compared to existing routes. Moreover, this approach is adaptable to similar logistics problems, offering a foundation for further research in multi-objective optimization for distribution systems. |
| format | Article |
| id | doaj-art-2f89131ffc3a43a48aece75736fd2200 |
| institution | OA Journals |
| issn | 2086-0382 2477-3344 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Mathematics Department UIN Maulana Malik Ibrahim Malang |
| record_format | Article |
| series | Cauchy: Jurnal Matematika Murni dan Aplikasi |
| spelling | doaj-art-2f89131ffc3a43a48aece75736fd22002025-08-20T02:13:45ZengMathematics Department UIN Maulana Malik Ibrahim MalangCauchy: Jurnal Matematika Murni dan Aplikasi2086-03822477-33442025-03-0110131232510.18860/cauchy.v10i1.315298662Optimization of Pertamax Fuel Distribution Using Clarke-Wright Savings, Nearest Neighbour, and Goal Programming (Case Study: Malang City)Tharisa Melani0Sobri Abusini1Marjono Marjono2Brawijaya UniversityBrawijaya UniversityBrawijaya UniversityFuel distribution optimization is crucial to meet growing demand and reduce operational costs, especially in cities like Malang, where vehicle numbers are increasing. This research addresses the distribution challenges of PT Pertamina, focusing on designing efficient routes to minimize distance, cost, and delivery time while meeting fuel demands effectively. The problem, classified as a Capacitated Vehicle Routing Problem (CVRP), is solved using the Clarke-Wright Savings (CWS), Nearest Neighbour (NN), and Goal Programming (GP). The CWS is applied to group routes efficiently by reducing travel distances, while NN determined the delivery sequence within each route. GP addressed multi-objective optimization, minimizing costs and delivery time, maximizing Pertashop demands, and optimizing vehicle use. The results show that the combination of CWS and NN algorithms reduced the total travel distance by 140 km, or 12.5% reduction. Additionally, the GP method optimized vehicle use to 13, achieving a 59.68% cost reduction and a 48.68% time savings. These findings highlight the effectiveness of combining these algorithms in fuel distribution optimization, providing a more efficient solution compared to existing routes. Moreover, this approach is adaptable to similar logistics problems, offering a foundation for further research in multi-objective optimization for distribution systems.https://ejournal.uin-malang.ac.id/index.php/Math/article/view/31529clarke-wright savingsdistributionfuel oilgoal programmingnearest neighbour |
| spellingShingle | Tharisa Melani Sobri Abusini Marjono Marjono Optimization of Pertamax Fuel Distribution Using Clarke-Wright Savings, Nearest Neighbour, and Goal Programming (Case Study: Malang City) Cauchy: Jurnal Matematika Murni dan Aplikasi clarke-wright savings distribution fuel oil goal programming nearest neighbour |
| title | Optimization of Pertamax Fuel Distribution Using Clarke-Wright Savings, Nearest Neighbour, and Goal Programming (Case Study: Malang City) |
| title_full | Optimization of Pertamax Fuel Distribution Using Clarke-Wright Savings, Nearest Neighbour, and Goal Programming (Case Study: Malang City) |
| title_fullStr | Optimization of Pertamax Fuel Distribution Using Clarke-Wright Savings, Nearest Neighbour, and Goal Programming (Case Study: Malang City) |
| title_full_unstemmed | Optimization of Pertamax Fuel Distribution Using Clarke-Wright Savings, Nearest Neighbour, and Goal Programming (Case Study: Malang City) |
| title_short | Optimization of Pertamax Fuel Distribution Using Clarke-Wright Savings, Nearest Neighbour, and Goal Programming (Case Study: Malang City) |
| title_sort | optimization of pertamax fuel distribution using clarke wright savings nearest neighbour and goal programming case study malang city |
| topic | clarke-wright savings distribution fuel oil goal programming nearest neighbour |
| url | https://ejournal.uin-malang.ac.id/index.php/Math/article/view/31529 |
| work_keys_str_mv | AT tharisamelani optimizationofpertamaxfueldistributionusingclarkewrightsavingsnearestneighbourandgoalprogrammingcasestudymalangcity AT sobriabusini optimizationofpertamaxfueldistributionusingclarkewrightsavingsnearestneighbourandgoalprogrammingcasestudymalangcity AT marjonomarjono optimizationofpertamaxfueldistributionusingclarkewrightsavingsnearestneighbourandgoalprogrammingcasestudymalangcity |