(COMBINATORIAL OPTIMIZATION & NETWORK ANALYSIS
- General structure of an optimization models, Different types of models
- Integer programming models
- Pyomo package in Python
- Different types of variables, constraints and objective functions
- One-directional and bi-directional indicators, Complementarity rule, Selective constraints, Not-equal and if-then constraints
- Linearization of multiplicative terms
- Reformulation of piecewise linear functions, absolute-value and fractional functions
- Relaxation, Totally Uni-modular models, Ideal formulation,
- Optimization over networks (Shortest path problem, Maximum flow problem, Minimum cost flow problem)
- Algorithms to solve Shortest path problem, Maximum flow problem and Minimum cost flow problem
- Valid cuts to improve the quality of models
- Bi-objective and bi-level models
- Infeasibility and unboundedness cases and dealing the unexpected results
- Combinatorial optimization models in practice
- Combinatorial optimization models in practice