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    ILLEGAL DUMPING RISK MITIGATION THROUGH SPATIAL ROAD NETWORK OPTIMIZATION FOR CONSTRUCTION WASTE MANAGEMENT

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    Fatima Al-Thani_ OGS Approved Thesis.pdf (2.403Mb)
    Date
    2025-06
    Author
    AL-THANI, FATIMA
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    Abstract
    Construction and Demolition Waste (CDW) management poses significant logistical and environmental challenges, necessitating an optimized transportation strategy that balances cost efficiency and environmental sustainability. This study develops a mixed-integer linear programming (MILP) model to minimize total transportation costs while reducing the risk of illegal dumping. The model incorporates distance, transportation costs, penalty value, and an impact factor that quantifies the potential illegal dumping risk for each route. The model was solved using the CBC MILP solver in Python (PuLP), yielding an optimal total transportation cost of 86,448,041 QAR. The highest cost contribution (63.4%) came from Zone 55, which manages over 1 million tons of waste, despite its relatively short distance of 34.9 km and moderate impact factor of 0.3655. Zone 57 contributed 21.7% of total costs, while Zone 80 accounted for 11.2% despite having the highest unit cost due to its 120.8 km distance and 0.7265 impact factor. A sensitivity analysis revealed a strong linear relationship between the impact factor cost parameter and total costs. When increasing this parameter from 50 to 500 QAR, total costs rose from approximately 270 million QAR to 2.5 billion QAR, with Zone 55 showing the most significant absolute sensitivity due to its high waste volume. Notably, the optimal path selection remained stable across all zones regardless of parameter changes. These findings highlight that optimized CDW transportation planning not only reduces costs but also ensures compliance with waste disposal regulations, mitigating illegal dumping risks. The research provides a decision-support tool for urban planners and policymakers to design efficient and sustainable waste management strategies. Future work will extend the model by integrating real-time traffic data, alternative waste treatment facilities, and dynamic regulatory constraints to enhance its practical applicability.
    DOI/handle
    http://hdl.handle.net/10576/66427
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    • Engineering Management [‎146‎ items ]

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