Optimization of Urban Cargo Distribution Network and Station Points with Open Source GIS Açık Kaynak CBS ile Şehiriçi Kargo İstasyon Noktalarının Optimizasyonu ve Dağıtım Planlaması

BEDİROĞLU, Şevket · 2021 · Crossref

DOI: 10.21605/cukurovaumfd.1040769

archive: archived pipeline: cataloged verified

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Summary

This study addresses the optimization of urban cargo distribution networks and station locations to improve resource management efficiency in the growing logistics sector. Motivated by the surge in e-commerce and the demand for fast, reliable delivery, the research focuses on minimizing time loss and fuel consumption through strategic site selection and route planning. The authors argue that Geographic Information Systems (GIS), particularly open-source tools and data, offer low-cost, effective solutions for these logistical challenges. The study was conducted in the Şehitkamil district of Gaziantep, Turkey, a region characterized by intense urbanization and logistics activity. The methodology utilized open-source GIS data, including road network maps with traffic density and direction information, as well as building and population data sourced from OpenStreetMap. The researchers analyzed the locations of a specific cargo company’s branches and their vehicle routes. To determine optimal station locations, isochrone maps were generated over the road network to depict areas accessible within specific time thresholds. These maps allowed for a balance between traffic conditions and population density. Additionally, vehicle responsibility zones were defined by calculating population values within 5, 10, and 15-minute access zones from each station. Finally, daily route planning was performed for over 100 cargo deliveries using network analysis to optimize paths based on dynamic daily data. The results demonstrated that the developed GIS-based system effectively optimized both station placement and daily vehicle routes. The use of isochrone maps provided significant advantages over classical buffer methods by establishing ideal correlations between population, road length, and traffic density. The analysis successfully determined vehicle liability zones based on population data and generated optimized daily routes that reduced time and fuel consumption. The study confirmed that integrating open-source GIS tools with decision-making processes allows for efficient modeling of the vehicle routing problem, a critical spatial logistical challenge. The significance of this research lies in its demonstration of how open-source GIS technologies can enhance urban cargo transportation efficiency. By leveraging freely available data and software, cargo companies can achieve better resource management, reduce operational losses, and increase customer satisfaction through timely deliveries. The findings suggest that web-based GIS systems and open-source datasets are viable, economical alternatives for logistics planning, contributing to the development of smart transportation systems. This approach supports sustainable development by optimizing physical flows and reducing the environmental impact of freight transportation through minimized fuel usage and improved route efficiency.

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• last mile delivery