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Updated: Jul 6, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Mathematical optimization of waste management systems: Methodological review and perspectives for application
Mexitli Sandoval-Reyes1, Rui He2, Rui Semeano3
1IN+/LARSyS, Centre for Innovation, Technology and Policy Research, Associação para a Investigação e Desenvolvimento do Instituto Superior Técnico, Universidade de Lisboa, Av. António José de Almeida, n.° 12, 1000-043 Lisboa, Portugal; Tecnologico de Monterrey, School of Engineering and Sciences, Ave. Eugenio Garza Sada 2501, Monterrey, N.L., 64849, Mexico.
This review standardizes waste management optimization models (WM-OMs) for circular economy transitions. It proposes a novel method to benchmark WM-OMs and enhance their accuracy and reliability for better decision-making.
Area of Science:
- Environmental Science
- Operations Research
- Industrial Ecology
Background:
- Sustainable waste management (WM) is crucial for circular economy transitions, with regional variations influenced by socioeconomic factors and infrastructure.
- Mathematical optimization models (WM-OMs) are vital tools for informing local waste management decisions and identifying policy interventions.
Purpose of the Study:
- To review and standardize the design of WM-OMs for waste valorization networks.
- To propose a novel characterization method for examining, relating, and benchmarking WM-OMs.
- To identify opportunities for improving the accuracy and reliability of future WM-OMs.
Main Methods:
- A systematic literature review of 58 articles published between 2015 and 2022 on WM-OMs.
- Development of a novel characterization method for WM-OMs.
- Assembly of a comprehensive database documenting WM-OM characteristics and case study data.
Main Results:
- Identified key areas for WM-OM improvement: modeling complex reactions, incorporating constraints (regulatory, environmental, political), recognizing the informal sector, exploring market impacts, enhancing data traceability, justifying uncertainty analysis (UA), and specifying model details.
- Provided a guide for selecting UA approaches, addressing a gap in current literature.
- Highlighted the need for balancing model complexity, performance, and practicality for stakeholders.
Conclusions:
- Standardizing WM-OMs through a robust characterization method enhances their utility for policy and decision-making.
- Future WM-OMs can be improved by addressing identified limitations and adopting best practices in modeling and data reporting.
- A stakeholder-centric approach is essential for developing practical and effective waste management optimization solutions.
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