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Research Group for Industrial Ecology & Systems Sustainability

Complex Systems and Industrial Ecology
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Integrated Methods and Complexity Models for Industrial Ecology and Sustainability
 
Industrial ecology endeavors to understand how the industrial system works, how it is regulated, and its interaction with the biosphere; then, on the basis of what we know about ecosystems, to determine how it could be restructured to make it compatible with the way natural ecosystems function. Much like ecosystems, man-made systems constantly evolve because individuals, organizations, governments decide on consumption, industrial design, (dis)investment and regulation respectively in response to and in interaction with their respective environment. (Journal of Industrial Ecology, 2008)

In complexity theory system evolution is a central paradigm. Under its banner, a range of methodologies and associated tools have been developed, such as artificial intelligence, multi-agent systems, agent-based modeling, system dynamics, evolutionary programming, genetic algorithm and hybrid modeling. It may therefore be seen that the use of complexity theory and tools has potential to shift the frontier of industrial ecology, by enhancing the quality of systems analysis and by underpinning recommendations for redirecting industrial development towards sustainability. (Journal of Industrial Ecology, 2008).

Research Plans

 Decision support for complex decisions characterized by multiple objectives under risk and uncertainty

 Decision making and strategic planning towards sustainable outcomes in industrial ecology modeled networks

 Process Modeling and Technology Development in Biorefinery

 

Collaboration

Center for Complex Adaptive Agent Systems Simulation

Forum for Science and Innovation for Sustainable Development