Modules

Prerequisites

Contents

Graphs, algorithmic problems on graphs (shortest path, spanning trees, Steiner trees, maximum flow, minimum cut, assignment, coloring, and others), Dantzig's simplex linear optimization method, non-linear optimization methods, integer optimization methods, multi-criteria (multi-objective) optimization, stochastic optimization, robust optimization, bilevel optimization, modeling languages to formulate optimization problems, analysis of case studies e.g. from the field of environmental sciences and resource management.

Learning outcomes

Students get familiar with basic concepts of mathematical optimization (in particular, linear, nonlinear, and mixed-integer optimization) and graph theoretic concepts. They will gain the ability to formalize an applied optimization problem e.g. from the field of environmental sciences and resource management and solve them with mathematical means, and will know how use computer software (modeling languages and solvers) to formulate and solve optimization problems.

Assessment

• 4 written examinations, 30 minutes each, of which the best 3 contribute to the final module grade with a weighting of 1/3 each

Remarks

• Study programme Environmental and Resource Management B.Sc.: Compulsory elective module • Study programme Environmental and Resource Management M.Sc.: Compulsory elective module • Study programme Physics M. Sc.: Compulsory elective module in complex „Minor Subject“