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This study investigates optimizing the placement of used cooking oil (UCO) containers in Valencia to improve urban recycling accessibility and promote environmental sustainability. The paper addresses the maximum covering location problem by proposing a genetic algorithm that utilizes real-world data to position UCO recycling bins throughout the city strategically. The goal is to enhance accessibility for residents while reducing operational costs and environmental impact. The methodology includes problem definition, hyperparameter optimization, and comparison of random and heuristic-guided initialization techniques for the genetic algorithm. Computational experiments demonstrate the proposed solutions’ effectiveness in refining container distribution.

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Optimizing UCO Container Placement in Urban Environments: A Genetic Algorithm Approach

  • 会议论文

  • 发表日期：

    2025年

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  • Joan C. Moreno,
  • Juan M. Alberola,
  • Victor Sanchez-Anguix,
  • Jaume Jordán,
  • Vicente Julián,
  • Vicent Botti

摘要

This study investigates optimizing the placement of used cooking oil (UCO) containers in Valencia to improve urban recycling accessibility and promote environmental sustainability. The paper addresses the maximum covering location problem by proposing a genetic algorithm that utilizes real-world data to position UCO recycling bins throughout the city strategically. The goal is to enhance accessibility for residents while reducing operational costs and environmental impact. The methodology includes problem definition, hyperparameter optimization, and comparison of random and heuristic-guided initialization techniques for the genetic algorithm. Computational experiments demonstrate the proposed solutions’ effectiveness in refining container distribution.