Date of Award
2014
Degree Type
Thesis
Degree Name
Master of Science in Industrial and Systems Engineering
Department
Mechanical, Industrial and Systems Engineering
First Advisor
Manbir Sodhi
Abstract
Recent publications call for a higher focus on implementation of the theoretical concept of industrial ecology. It embodies the idea that collaborating companies use each other’s waste and byproducts following the example of the natural metabolism. Subject matter of this work is the practical application of this idea, i.e. eco-industrial parks and networks. In addition to the positive impact on the environment due to a reduction of pressure on limited natural resources, existing cases show that benefits can simultaneously be achieved for all three dimensions of sustainable development, including the economy and society.
In order to promote this concept and thus facilitate the implementation of sustainable development in the private sector, this thesis proposes an Interactive Optimized Negotiation Algorithm (IONA) embedding a mixed-integer linear program with weighted achievement functions. This flexible network model supports the establishment of new industrial ecology in practice. It can flexibly be adapted to various circumstances and overcomes major critiques of existing approaches. In addition to the computer implementation of this advanced modeling approach, this work provides a catalogue of requirements to meet when modeling industrial ecology.
The approach considers multiple objectives, different stakeholder interests, and various material flow types. The closing study of two cases shows the comprehensive capabilities of the program. Exceeding the scope of this work, the computer program can be used to conduct studies of existing networks regarding their stability when facing today’s increasing necessity to set and meet environmental and social objectives.
Recommended Citation
Schulze, Fabian, "CLASSIFICATION AND DEVELOPMENT OF MATHEMATICAL MODELS AND SIMULATION FOR INDUSTRIAL ECOLOGY" (2014). Open Access Master's Theses. Paper 367.
https://digitalcommons.uri.edu/theses/367
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