Disc. Optimization·Course
Discrete Optimization
Discrete optimization: integer programming, branch and bound, network flows, metaheuristics, and approximation algorithms
4
Modules
12
Articles
~1 h
Reading
IV
CLOs
§ 01 — Curriculum
4 modules.
Each module is a small unit. Most read in sequence — but a determined reader can begin anywhere.
- M IFundamentals of Discrete Optimization and CombinatoricsIntroduction to discrete optimization, classical problems, and complexity theory3 articles
18 minBegin → - M IIBranch-and-Bound MethodsBranch-and-Bound, Branch-and-Cut, and their applications in MILP3 articles
18 minBegin → - M IIIApproximation AlgorithmsApproximation theory, greedy algorithms, and PTAS3 articles
18 minBegin → - M IVMetaheuristicsSimulated annealing, genetic algorithms, and local search3 articles
18 minBegin →
§ 02 — Learning outcomes
4 outcomes.
CLO I
Integer Programming
Formulate problems as integer linear programs and apply LP relaxation and branch-and-bound methods
CLO II
Network Algorithms
Solve maximum flow, shortest path, and matching problems
CLO III
Metaheuristics
Apply simulated annealing, genetic algorithms, and tabu search
CLO IV
Applications
Solve practical routing, scheduling, and resource allocation problems
§ 03 — Practices