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<p>This study models garbage collection in a local city in Hokkaido, Japan, driven by the increasing burden of collection costs despite a declining population. A unique problem in this city is the large number of garbage stations, which exacerbates the collection burden. We examine the impact of waste volume fluctuations and the number and layout of garbage stations on collection routes and costs to find solutions to this issue. This research aims to develop cost-effective and feasible garbage collection strategies to support evidence-based policymaking. We formulated a garbage collection challenge using mixed integer linear programming to minimize travel distances and operational burdens within vehicle capacity constraints. Numerical simulations reveal significant findings: (i) optimized routes reduce total travel distance by <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10015_2024_988_Article_IEq1.gif" Format="GIF" Height="6" Rendition="HTML" Resolution="72" Type="Linedraw" Width="17" /> </InlineMediaObject> <EquationSource Format="TEX">\(\sim\)</EquationSource> <EquationSource Format="MATHML"><math> <mo>∼</mo> </math></EquationSource> </InlineEquation>25% compared to existing routes, (ii) increased waste volumes lead to non-linear increases in route lengths, and (iii) the aggregation strength of garbage stations significantly impacts route efficiency and the number of required stations. Conclusively, this study provides empirical evidence to guide policymakers in optimizing garbage collection systems, ensuring effective resource utilization and maintaining service quality.</p>

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Optimization of garbage collection routes for evidence-based policy-making

  • 期刊论文

  • 发表日期：

    2025年1月11日

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  • Tomoki Kaho,
  • Kazutoshi Sakakibara,
  • Mikiharu Arimura,
  • Shinya Watanabe

摘要

This study models garbage collection in a local city in Hokkaido, Japan, driven by the increasing burden of collection costs despite a declining population. A unique problem in this city is the large number of garbage stations, which exacerbates the collection burden. We examine the impact of waste volume fluctuations and the number and layout of garbage stations on collection routes and costs to find solutions to this issue. This research aims to develop cost-effective and feasible garbage collection strategies to support evidence-based policymaking. We formulated a garbage collection challenge using mixed integer linear programming to minimize travel distances and operational burdens within vehicle capacity constraints. Numerical simulations reveal significant findings: (i) optimized routes reduce total travel distance by \(\sim\) ∼ 25% compared to existing routes, (ii) increased waste volumes lead to non-linear increases in route lengths, and (iii) the aggregation strength of garbage stations significantly impacts route efficiency and the number of required stations. Conclusively, this study provides empirical evidence to guide policymakers in optimizing garbage collection systems, ensuring effective resource utilization and maintaining service quality.