This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...
where \(\mathsf{G}(\cdot)\) is some convex operator and \(\mathcal{F}\) is as set of feasible input distributions. Examples of such an optimization problem include finding capacity in information ...
Introduction to a wide range of computational techniques for engineering design. Modeling, simulation, optimization, design software, examples/projects with emphasis on computational techniques for ...
Fruchter, G. (2026) Opportunism in Supply Chain Recommendations: A Dynamic Optimization Approach. Modern Economy, 17, 26-38.
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