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Pasaribu, Melly Rosinta
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Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Environmental Science

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Optimasi Rute Distribusi pada Heterogeneous Capacitated Vehicle Routing Problem (HCVRP) Menggunakan Algoritma Evolutionary (Studi Kasus: CV. XYZ) Willis, Tito Bisma May; Pasaribu, Melly Rosinta; Sandra, Al Dian Devina; Miftah, Tarizza Alya Nurul
SPECTA Journal of Technology Vol. 9 No. 3 (2025): Specta Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/specta.v9i3.8481430

Abstract

CV. XYZ is a company engaged in the field of goods delivery services that must distribute to various customer points every day. With the number of vehicles and delivery routes that continue to grow, the company faces challenges in managing efficient routes. If delivery is carried out without optimal route planning, there can be wasted mileage, increased fuel costs, and delays in delivery that can reduce customer satisfaction. This study tries to provide a solution with a combination approach between the Capacitated Vehicle Routing Problem (CVRP) and Heterogeneous Vehicle Routing Problem (HVRP) methods using the Evolutionary Algorithm feature in Microsoft Excel. The main problem to be answered in this study is how to determine the most optimal route and how much distance savings are obtained from the optimization results. The steps in the study start from initial observation, collecting customer and vehicle data, creating a route model, processing data with Excel, to analyzing the results. From the optimization results, the total initial mileage before optimization was 318.7 km, which was then successfully reduced to 300.44 km after processing with Solver, resulting in a difference savings of 18.26 km. These findings indicate that a mathematical method approach in delivery route planning can have a significant impact on the company's distribution efficiency and operational costs.
Co-Authors Miftah, Tarizza Alya Nurul Sandra, Al Dian Devina Willis, Tito Bisma May