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Dealing with Uncertainty in Optimization-Based Decision Support Applications using AIMMS
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Data uncertainty is ubiquitous in business applications and inherent in decision support optimization models. Uncertainty can be dealt with using techniques like parametric analysis, scenario analysis, stochastic programming or robust optimization.
In this webinar we share essential modeling, solution, and visualization aspects for decision making under uncertainty using AIMMS. Based on some representative examples, we illustrate how specialized AIMMS features tailored to the above techniques may be employed for dealing with uncertainty in optimization-based decision support systems.
In this webinar we share essential modeling, solution, and visualization aspects for decision making under uncertainty using AIMMS. Based on some representative examples, we illustrate how specialized AIMMS features tailored to the above techniques may be employed for dealing with uncertainty in optimization-based decision support systems.
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