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  1. Home
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  4. Variational Approaches and Mathematical Models for Food Waste Management
 
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Variational Approaches and Mathematical Models for Food Waste Management

Date Issued
2024
Author(s)
Leong, Mei Kei
Faculty of Business and Law 
Abstract
The global food industry generates substantial waste, posing significant environmental, economic, and social challenges. This dissertation explores circular business strategies for food waste management, aiming to develop an efficient model that integrates circular economy principles and innovative technologies. Key research questions include: What are current food waste management practices? How can circular economy principles reduce food waste effectively? What role can technology play in improving these systems? The study also examines barriers to implementation and identifies gaps in existing literature. The methodology involves a comprehensive literature review, case studies, and the development of a detailed mathematical model. The literature review covers circular economy concepts, current food waste treatment technologies, machine learning and Al applications in waste management. Case studies from various countries provide insights into regulatory frameworks and innovative solutions. Central to this research is the mathematical modelling of food waste management systems. The model employs Hamiltonian and/or Lagrangian formulations to optimise waste transportation and processing. This approach allows for the simulation of various scenarios, helping to identify the most efficient pathways for food waste reduction and resource recovery. The model also incorporates phase transitions better to understand the dynamics of waste generation and treatment processes. Phase transitions mark changes on tendencies and in this case they help us to evaluate the viability of the construction of a fast track for the transportation of food waste in any city. Results indicate that adopting circular economy principles in food waste management is feasible and beneficial. Effective strategies include bioplastics, insectutilisation, and machine learning models for waste prediction and management. The developed mathematical model suggests efficient waste transportation through a coupled network approach, ensuring rapid and effective waste evacuation. The research highlights the importance of technological integration and cross-sector collaboration for sustainable food waste management. It also stresses the need for robust regulatory frameworks and consumer education to drive behavioural changes and support circular practices.
Subjects

Food Waste Management...

Transportation Mathem...

Quantum Mechanics

Machine Learning and ...

Social and Governance...

Environmental

Consumer behaviour

Sustainable Business ...

Circular Economy

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M-BA 2024 LEO,MEI.pdf

Size

2.39 MB

Format

Adobe PDF

Checksum

(MD5):bb13de9b80369b45be7c176f003520f2


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