Advanced methods of mathematical programming

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Department of Smart Cities and Regions

Synopsis:

Linear programming methods for solving optimization problems with one criterion (simplex method, branch and bound method, Gomory algorithms, column generation method, Benders decomposition method, sensitivity analysis)

Linear programming methods for solving optimization problems with multiple criteria (scalarization method, sequential optimization according to criteria preference, STEM, criteria aggregation method)

Nonlinear programming methods for solving optimization problems with one criterion without relations (gradient methods, Davidon-Fletcher-Powell method)

Nonlinear programming methods for solving optimization problems with one criterion and with relations (Lagrange multipliers method, reduced gradient methods - Wolfe's method).

Transformation of nonlinear optimization models into linear models.

Multilevel mathematical programming

Dynamic programming

Compromise and composite programming

Goal programming

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The course is a part of the following study plans: