Solving Inventory Routing Problems with Crow Search Algorithm
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| Titel: | Solving Inventory Routing Problems with Crow Search Algorithm |
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| Autoren: | Krisnawati, Maria, Chris Monita, Ayu, Sofiana, Amanda |
| Verlagsinformationen: | Islamic Azad University Press, 2025. |
| Publikationsjahr: | 2025 |
| Schlagwörter: | Transportation costs, Inventory cost, Crow search algorithm, Inventory routing problem |
| Beschreibung: | The intensifying competition in the business environment compels companies to proactively retain customers by minimizing costs across all aspects while upholding product or service quality. Given the pivotal role of inventory control in cost optimization, a good management of inventory levels becomes priority. Employing a strategic approach within supply chain management, specifically the Inventory Routing Problem (IRP), proves instrumental in achieving an optimal balance in inventory that subsequently impacts cost minimization. The IRP integrates inventory management with vehicle routing to enhance efficiency. In this research, the IRP was applied through the application of the Crow Search Algorithm (CSA), a method inspired by the foraging and caching behaviors of crows. By emulating these natural habits, the CSA method aims to deliver an optimal distribution schedule that minimizes both inventory and transportation costs. The study relied on secondary data in the form of a comprehensive database encompassing relevant data and solution outcomes. The solutions derived from the database serve as a benchmark for evaluating the efficacy of the CSA method. The findings of the research revealed that the total cost incurred through the implementation of the CSA method is notably lower than that obtained from the database results. Furthermore, the simulation results indicate no significant difference between the CSA method and the database, affirming the applicability of the CSA method for effectively addressing IRP. Journal of Industrial Engineering International,21(2),41 |
| Publikationsart: | Article |
| Sprache: | English |
| DOI: | 10.82374/jiei.2025.1039608 |
| Rights: | CC BY |
| Dokumentencode: | edsair.doi...........933b5e05ced3475632c1130fa18c66d1 |
| Datenbank: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstract: | The intensifying competition in the business environment compels companies to proactively retain customers by minimizing costs across all aspects while upholding product or service quality. Given the pivotal role of inventory control in cost optimization, a good management of inventory levels becomes priority. Employing a strategic approach within supply chain management, specifically the Inventory Routing Problem (IRP), proves instrumental in achieving an optimal balance in inventory that subsequently impacts cost minimization. The IRP integrates inventory management with vehicle routing to enhance efficiency. In this research, the IRP was applied through the application of the Crow Search Algorithm (CSA), a method inspired by the foraging and caching behaviors of crows. By emulating these natural habits, the CSA method aims to deliver an optimal distribution schedule that minimizes both inventory and transportation costs. The study relied on secondary data in the form of a comprehensive database encompassing relevant data and solution outcomes. The solutions derived from the database serve as a benchmark for evaluating the efficacy of the CSA method. The findings of the research revealed that the total cost incurred through the implementation of the CSA method is notably lower than that obtained from the database results. Furthermore, the simulation results indicate no significant difference between the CSA method and the database, affirming the applicability of the CSA method for effectively addressing IRP.<br />Journal of Industrial Engineering International,21(2),41 |
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| DOI: | 10.82374/jiei.2025.1039608 |