Sustainable hazardous waste management: a two-stage dynamic multi-period decision framework

This thesis presents a comprehensive two-stage dynamic multi-period decision framework for sustainable hazardous waste management. The first stage involves optimizing the location and allocation of waste treatment facilities with a focus on minimizing both cost and emission. The second stage contains a dynamic multi-period vehicle routing problem (DMPVRP), which allows for real-time adjustments based on variable pickup dates to cope with dynamics, such that cost, risk, and emission are simultaneously minimized. Trade-ofs between these objectives are managed by assigning weight to each objective in both stages. A case study of the healthcare waste management network in Shanghai, China, demonstrates the model’s applicability and efectiveness. Results indicate that the proposed system signifcantly improves cost efciency, reduces environmental impact, and minimizes risk to human health compared to the current system. Sensitivity analyses further validate the robustness of the proposed framework, showing improvements across all aspects. This research provides valuable insights for policymakers and waste management authorities aiming to enhance the sustainability and resilience of hazardous waste management systems.

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Publication Details

Journal
Memorial University Research Repository (Memorial University)
Published
2025-02-17
DOI
https://doi.org/10.48336/1fyv-a291
Primary Topic
Vehicle Routing Optimization Methods
Type
article
Field-Weighted Citation Impact
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article

Sustainable hazardous waste management: a two-stage dynamic multi-period decision framework

Memorial University Research Repository (Memorial University)
Vehicle Routing Optimization Methods
article

Sustainable hazardous waste management: a two-stage dynamic multi-period decision framework

article en

Abstract

This thesis presents a comprehensive two-stage dynamic multi-period decision framework for sustainable hazardous waste management. The first stage involves optimizing the location and allocation of waste treatment facilities with a focus on minimizing both cost and emission. The second stage contains a dynamic multi-period vehicle routing problem (DMPVRP), which allows for real-time adjustments based on variable pickup dates to cope with dynamics, such that cost, risk, and emission are simultaneously minimized. Trade-ofs between these objectives are managed by assigning weight to each objective in both stages. A case study of the healthcare waste management network in Shanghai, China, demonstrates the model’s applicability and efectiveness. Results indicate that the proposed system signifcantly improves cost efciency, reduces environmental impact, and minimizes risk to human health compared to the current system. Sensitivity analyses further validate the robustness of the proposed framework, showing improvements across all aspects. This research provides valuable insights for policymakers and waste management authorities aiming to enhance the sustainability and resilience of hazardous waste management systems.

Memorial University Research Repository (Memorial University)
Memorial University of Newfoundland (CA)
Openalex Percentile: Top 45%
Vehicle Routing Optimization Methods
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