Application of CVRP Using a Genetic Algorithm Approach to Optimize Last-Mile Delivery Costs (Case Study at the PT Pos Indonesia)

Dicky Dianta Sitepu; Melia Eka Lestiani; Agus Purnomo

doi:10.63922/ijevss.v5i03.5897

Dicky Dianta Sitepu Universitas Logistik dan Bisnis Internasional
Melia Eka Lestiani Universitas Logistik dan Bisnis Internasional
Agus Purnomo Universitas Logistik dan Bisnis Internasional

DOI: https://doi.org/10.63922/ijevss.v5i03.5897

Keywords: Last Mile Delivery, Outsourcing vs. In-house, Clusters, CVRP, Clarke and Wright Savings, Genetic Algorithm

Abstract

The logistics industry is currently grappling with substantial challenges, primarily due to intensifying price competition, a phenomenon that is being predominantly Fueled by the continuous expansion of the e-commerce sector. It has been determined that delivery costs for Last Mile Delivery (LMD) activities can account for between 28 and 60 per cent of total logistics costs, thus indicating that this area is of critical importance with regard to optimization. PT Pos Indonesia is confronted with a significant challenge in preserving price competitiveness within this evolving market. The objective of this study is to make a comparison between the costs of LMD operations in two different models. The initial strategy entails the externalization of operations, wherein a success-based fee is levied for each completed package. The second strategy involves the implementation of an in-house model, where transportation vehicles and human resources are managed internally, in conjunction with route optimization utilizing CVRP. The present study employs a research methodology that entails the calculation of the cost per package for both models. This calculation encompasses CAPEX, OPEX and potential operation uncertainties risks. This study's findings indicate the viability of implementing the in-house operational model to achieve a reduction in monthly expenses of up to 7.11% (Rp. 1,920,162). Furthermore, the application of CVRP in conjunction with the Genetic Algorithm method has been shown to result in significant savings, including a reduction in travel distance by 142.6 km and an improvement in delivery time by 381 minutes when compared to the outsourcing operational model. It is anticipated that the study will furnish PT Pos Indonesia with strategic recommendations for the determination of the most optimal operational model for LMD activities, with a view to enhancing the company's efficiency and competitiveness in the future.

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