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Commit c9ef2dfe authored by Gabriel Gehrke's avatar Gabriel Gehrke
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removed the unfinished max flow problem

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examples/mixed_integer_programming/multi_source_sink_max_flow/maxflow.ipynb deleted 100644 → 0
+ 0
− 106
View file @ 03ce64d3
%% Cell type:code id: tags:
``` python
from model import MultiSourceSinkMaxFlow
import itertools
import random
```
%% Cell type:code id: tags:
``` python
instance = MultiSourceSinkMaxFlow()
# define source and sink nodes
instance.add_source("S1")
instance.add_source("S2")
instance.add_sink("T1")
instance.add_sink("T2")
instance.add_edge("S1", "A", capacity=35.7)
instance.add_edge("S1", "D", capacity=59.0)
instance.add_edge("S2", "B", capacity=20.3)
instance.add_edge("S2", "C", capacity=47.38)
instance.add_edge("A", "B", capacity=9.8)
instance.add_edge("B", "D", capacity=50.5)
instance.add_edge("C", "D", capacity=50.0)
instance.add_edge("D", "T2", capacity=100.0)
```
%% Cell type:code id: tags:
``` python
solution = instance.optimize()
instance.draw(utilizations=solution)
```
%% Output
Set parameter Username
Academic license - for non-commercial use only - expires 2023-12-04
Gurobi Optimizer version 9.5.2 build v9.5.2rc0 (linux64)
Thread count: 12 physical cores, 24 logical processors, using up to 24 threads
Optimize a model with 4 rows, 8 columns and 11 nonzeros
Model fingerprint: 0x6d47b9d0
Coefficient statistics:
Matrix range [1e+00, 1e+00]
Objective range [1e+00, 1e+00]
Bounds range [1e+01, 1e+02]
RHS range [0e+00, 0e+00]
Presolve removed 4 rows and 8 columns
Presolve time: 0.00s
Presolve: All rows and columns removed
Iteration Objective Primal Inf. Dual Inf. Time
0 1.0000000e+02 0.000000e+00 0.000000e+00 0s
Solved in 0 iterations and 0.00 seconds (0.00 work units)
Optimal objective 1.000000000e+02
examples/mixed_integer_programming/multi_source_sink_max_flow/model.py deleted 100644 → 0
+ 0
− 81
View file @ 03ce64d3
import gurobipy as gp
from gurobipy import GRB
import networkx as nx
from typing import Any, List, Set, Tuple, Dict
import matplotlib.pyplot as plt
Node = Any
Edge = Tuple[Node, Node]
class MultiSourceSinkMaxFlow():
def __init__(self) -> None:
self.graph = nx.DiGraph()
self.sources = set()
self.sinks = set()
def add_node(self, node: Node):
self.graph.add_node(node)
def add_source(self, node: Node):
self.add_node(node)
self.sources.add(node)
def add_sink(self, node: Node):
self.add_node(node)
self.sinks.add(node)
def add_edge(self, node1: Node, node2: Node, capacity: float):
assert not self.graph.has_edge(node1, node2)
self.graph.add_edge(node1, node2, capacity=capacity)
def optimize(self):
m = gp.Model()
edge_utilization_vars = {
(p, q): m.addVar(lb=0.0, ub=self.graph[p][q]["capacity"], vtype=GRB.CONTINUOUS) for (p, q) in self.graph.edges()
}
target_term = 0.0
for v in self.graph.nodes():
if v in self.sources:
continue
elif v in self.sinks:
incoming_edges = self.graph.in_edges(v, data=False)
incoming_flow = sum(edge_utilization_vars[e] for e in incoming_edges)
target_term += incoming_flow
continue
incoming_edges = self.graph.in_edges(v, data=False)
outgoing_edges = self.graph.out_edges(v, data=False)
in_sum = sum(edge_utilization_vars[e] for e in incoming_edges)
out_sum = sum(edge_utilization_vars[e] for e in outgoing_edges)
m.addConstr(in_sum == out_sum)
m.setObjective(target_term, GRB.MAXIMIZE)
m.optimize()
utilizations = {e: var.X for e, var in edge_utilization_vars.items()}
return utilizations
def draw(self, utilizations: Dict[Edge, float]):
fig = plt.figure()
fig.set_size_inches(12, 12)
edge_labels = {
e: f"{round(util, 2)} / {round(self.graph[e[0]][e[1]]['capacity'], 2)}" for e, util in utilizations.items()
}
layout = nx.layout.planar_layout(self.graph)
nx.draw_networkx(
self.graph,
labels={n: str(n) for n in self.graph.nodes()},
pos=layout,
node_color=["orange" if n in self.sinks else ("green" if n in self.sources else "grey") for n in self.graph.nodes()]
)
nx.draw_networkx_edge_labels(self.graph, pos=layout, edge_labels=edge_labels, font_size=10)
plt.show()
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