https://github.com/balta2ar/discrete-optimization-001
Coursera Discrete Optimization course programming assignments source code
https://github.com/balta2ar/discrete-optimization-001
Last synced: 7 months ago
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Coursera Discrete Optimization course programming assignments source code
- Host: GitHub
- URL: https://github.com/balta2ar/discrete-optimization-001
- Owner: balta2ar
- Created: 2013-09-02T07:24:29.000Z (about 12 years ago)
- Default Branch: master
- Last Pushed: 2013-09-02T08:22:08.000Z (about 12 years ago)
- Last Synced: 2023-03-25T13:40:06.934Z (over 2 years ago)
- Language: Go
- Size: 30.8 MB
- Stars: 27
- Watchers: 4
- Forks: 26
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
discrete-optimization-001
=========================
## Coursera [Discrete Optimization](https://class.coursera.org/optimization-001/class/index) course programming assignments source code
Below is a list of optimization techniques/topics and languages used for each assignment.
Note that all assignments come with default trivial solution in python -- I don't count
python unless I implemented something non-trivial in this assignment. Also,
I started almost every assignment with implementing greedy or random solver,
I don't count them either.
#### Knapsack
- Go (DP, BnB solver)
- Dynamic Programming (DP)
- Branch and Bound (BnB)
#### Graph Coloring (GC)
- Bash (wrapper)
- Go (CP solver)
- Constraint Programming (CP)
- Minimum Remaining Variable (MRV)
- Least Constraining Value (LCV)
- Arc Consistency (AC3)
#### Traveling Salesman Problem (TSP)
- Bash (wrapper)
- Go (LS solver)
- R (visualization)
- Python
- visualization (igraph)
- MIP problem generator, parser
- scipy.kmeans
- Local Search (LS)
- Simulated Annealing (SA)
- Metropolis
- 2-opt
- [Late Acceptance Hill Climbing](http://www.cs.stir.ac.uk/research/publications/techreps/pdf/TR192.pdf)
- Mixed Integer Programming (MIP)
- external solver: [SCIP](http://scip.zib.de)
- problem format: PIP
- problem formulations: Miller-Tucker-Zemlin, subtour elimination
#### Warehouse Location Problem (WLP)
- Bash (wrapper)
- Python (MIP problem generator, parser)
- Mixed Integer Programming (MIP)
- external solver: [SCIP](http://scip.zib.de)
- problem format: PIP
- problem formulations: SimpleModel, LectureModel
#### Vehicle Routing Problem (VRP)
- Bash (wrapper)
- Go (LS solver, unit test)
- R (visualization)
- Python (MIP problem generator, parser)
- Local Search (LS)
- Simulated Annealing (SA)
- Metropolis
- neighbour generation moves: 1. move customer from one route to another 2. swap two customers
- Mixed Integer Programming (MIP)
- external solver: [SCIP](http://scip.zib.de)
- problem format: PIP
- problem formulations: AssignCustomersModel (similar to WLP), OrderCustomersModel (similar to TSP)
#### Puzzle Challenge (PC)
- Python (nqueens CP solver back from university times)
- Octave (magic square)
- Constraint Programming (CP)
- Minimum Remaining Variable (MRV)
- Least Constraining Value (LCV)