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Using Dantzig-Wolfe (DW) decomposition algorithm to solve MCNF(Multi Commodity Network Flow) problem. Final project for the course of (large-scale) linear programming.

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Multi Commodity Network Flow

Using Dantzig-Wolfe decomposition algorithm to solve MCNF(Multi Commodity Network Flow) problem. Final project for the course of (large-scale) linear programming.

Background

We know the structure of urban road network and people's travel demand. There is limited capacity on each road segment. We assume that (1) the influence of the traffic flow on the road segment on the road travel time (i.e., the congestion effect) is not considered; (2) all vehicles are dispatched by a central decision maker (i.e., no game exists). Then how to arrange the route selection between each pair of origin-destination (OD) and the traffic flow on each route so that the sum of travel costs between all OD pairs is minimized?

Program

Required packages: numpy, pandas, gurobipy

  1. main.py: Main code of the algorithm
  2. draw.ipynb: Code to display the results
  3. network/: File folder storing the network and demand data
  4. output/: Output of the algorithm

Explanation of the Algorithm

See here (in Chinese). Comment on code in English.

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Using Dantzig-Wolfe (DW) decomposition algorithm to solve MCNF(Multi Commodity Network Flow) problem. Final project for the course of (large-scale) linear programming.

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