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Optimization of recycling bin placement using OpenStreetMap data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F25%3A00384029" target="_blank" >RIV/68407700:21260/25:00384029 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/11037695" target="_blank" >https://ieeexplore.ieee.org/document/11037695</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/SCSP65598.2025.11037695" target="_blank" >10.1109/SCSP65598.2025.11037695</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Optimization of recycling bin placement using OpenStreetMap data

  • Original language description

    This study presents an optimization approach for improving the placement of recycling bins in the town of Plasy using a graph-theoretic model. The problem is formulated as a p-median facility location problem, using OpenStreetMap data to analyze urban infrastructure. Two optimization criteria are considered: the first minimizes the total distance from residential buildings to the nearest recycling bin, while the second incorporates population-weighted distances based on the number of apartments per building. Several variants are evaluated, ranging from redistributing existing bins to adding new collection points. The results demonstrate that optimized placement can reduce average walking distances by up to 18% without excessive infrastructure expansion. The findings provide a cost-effective methodology for municipalities seeking to enhance waste collection accessibility while balancing operational efficiency and infrastructure investments.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    21100 - Other engineering and technologies

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2025 Smart City Symposium Prague - IEEE proceedings

  • ISBN

    979-8-3315-2551-4

  • ISSN

    2831-5618

  • e-ISSN

    2691-3666

  • Number of pages

    6

  • Pages from-to

  • Publisher name

    IEEE Press

  • Place of publication

    New York

  • Event location

    Prague

  • Event date

    May 29, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article