Second International Conference June 29 - July 2,
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Short Courses
To register for any of the four full-day Short Courses, make your selection at the time of registration. Space is limited in each course, so please register early. Pre-Conference Short Courses: Full-day Sunday Short Course $ 100, includes lunch Each full-day course runs from 9:00am - 3:00pm, Sunday, June 29, 2003 with a lunch break from Noon to 1:00pm. Course Descriptions: Life cycle inventory (LCI) modeling can be based on process models
or economic input output models. Each of these above methods has
its strengths and weaknesses. That is why the current application
frontier represents syntheses of both methods, "hybrid"
LCA. The purpose of this course is to enable attendees to develop
a practical and solid basis of understanding and familiarity with
process LCA, IO LCA, and hybrid methods. A computer lab will be
provided for the course. Designing
and Operating Eco-Industrial Parks System
Dynamics in Industrial Ecology System Dynamics was developed during the 50ies by Jay W. Forrester
at MIT. Originally developed to solve complex management problems
within industry, it turned out to be a general method that could
be applied in many areas, from industrial management problems to
global environmental problems, urban planning, energy planning etc.
The most famous studies are Limits to Growth, Urban Dynamics and
Industrial Dynamics. The course will introduce system dynamics using
a computer modeling environment developed especially for system
dynamics. Examples will illustrate how the dynamic modeling of stocks
and flows in system dynamics can address problems in industrial
ecology. Industrial
Ecology And Optimization This course provides an introduction to the optimization methods
and tools to be used in the various areas of industrial ecology.
It is a broad course designed to address the interdisciplinary nature
of industrial ecology. The course covers wide variety of topics
starting with linear programming, nonlinear programming, discrete
optimization, multi-objective optimization, and optimization under
uncertainty.
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