Abstract
Product distribution for companies in the industrial sector is an important issue as it is necessary to increase customer satisfaction and reduce costs. In this study, Nondominated-Sorting Genetic Algorithm II is used to solve Capacitated Vehicle Routing Problem in a case study dataset from the biggest fertilizer company in Indonesia. NSGA-II algorithm reduced the need for vehicles in product distribution with an advantage of 44.7%, while GWO algorithm yielded better results with an increase of time of 16.9%.
| Original language | English |
|---|---|
| Pages (from-to) | 420-427 |
| Number of pages | 8 |
| Journal | Procedia Computer Science |
| Volume | 234 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 7th Information Systems International Conference, ISICO 2023 - Washington, United States Duration: 26 Jul 2023 → 28 Jul 2023 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger -
SDG 8 Decent Work and Economic Growth -
SDG 12 Responsible Consumption and Production
Keywords
- Capacitated Vehicle Routing Problem
- Grey Wolf Optimizer
- NSGA-II
- Resource Efficiency
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