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This paper presents a constraint-aware framework for optimizing rural liquid product collection using a customized OR-Tools approach to solve the Capacitated Vehicle Routing Problem (CVRP). The system addresses real-world challenges like vehicle accessibility, voltage compatibility, product segregation, and variable collection frequencies, dynamically assigning a heterogeneous fleet to maximize fill rates (achieving 93.6% efficiency) and minimize route durations while ensuring feasibility. Tested on operational data, it achieved 100% POI (Point of Interest) coverage, eliminated manual revisions, and included practical features like automated Excel exports and interactive route visualization. The framework is designed for deployment in resource-sensitive, rule-heavy supply chains.

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AI-Enhanced Constraint-Aware Routing for Rural Liquid Collection: A Hybrid Optimization Framework

  • 会议论文

  • 发表日期：

    2026年

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  • Soufiane Reguemali,
  • Abdellatif Moussaid,
  • Younes Traouki,
  • abdelmajid Elouadi

摘要

This paper presents a constraint-aware framework for optimizing rural liquid product collection using a customized OR-Tools approach to solve the Capacitated Vehicle Routing Problem (CVRP). The system addresses real-world challenges like vehicle accessibility, voltage compatibility, product segregation, and variable collection frequencies, dynamically assigning a heterogeneous fleet to maximize fill rates (achieving 93.6% efficiency) and minimize route durations while ensuring feasibility. Tested on operational data, it achieved 100% POI (Point of Interest) coverage, eliminated manual revisions, and included practical features like automated Excel exports and interactive route visualization. The framework is designed for deployment in resource-sensitive, rule-heavy supply chains.