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MIE697S - (Spring semester)- Syllabus
This class will look at optimization problems related to stochastic systems for which the analytical form of the objective function are not known or are too complex to formulate. But the value of the function can be evaluated at specific points of the decision variables through simulation, and the problem can be solved using numerical optimization techniques. We will learn multiple algorithms for solving such problems. We will look at both static systems (parametric optimization) and dynamic systems (control optimization).
MIE397H - Tech elective for MIE students (Fall semester)- Syllabus
Simulation Modeling for Addressing Societal Problems
This course introduces students to the concepts and types of dynamic systems simulation modeling for addressing global problems where multiple interacting factors make analytically solving infeasible. Examples will include prevention and control of infectious disease outbreaks, population-level impact of cancer screening, and impact of carbon emissions and control on global temperature. For the class project students can choose other similar areas of application. The course will cover two main types of simulation modeling, compartmental and agent-based. We will use Netlogo, MATLAB, and Excel software.
MIE290H- Counts as GenEd -SB/G (Spring semester - Syllabus)
Infections and Social Determinants: Simulation Modeling for Disease Prevention
Social, behavioral, and environmental conditions are determining factors in people’s risk of illness. Systems simulation models that incorporate these determinants will provide a holistic systems thinking approach to analyzing alternative disease intervention strategies. These analyses can inform public health policy. Students in this class will learn about social determinants of health, systems thinking for disease prevention, the dynamics of infectious disease transmission, and construction of simple simulation models for disease prediction and control.
Contact: Professor Chaitra Goplappa, chaitrag(at)umass(dot)edu