A parallel branch-and-bound engine for Python
Project description
A parallel branch-and-bound engine for Python. (https://pybnb.readthedocs.io)
This software is copyright (c) by Gabriel A. Hackebeil (gabe.hackebeil@gmail.com).
This software is released under the MIT software license. This license, including disclaimer, is available in the ‘LICENSE’ file.
Quick Start
Define a problem:
# simple.py
import pybnb
class Simple(pybnb.Problem):
def __init__(self):
self.bounds = [0.0,1.0]
def sense(self):
return pybnb.minimize
def objective(self):
return round(self.bounds[1] - self.bounds[0], 3)
def bound(self):
return -(self.bounds[1] - self.bounds[0])**2
def save_state(self, node):
node.state = self.bounds
def load_state(self, node):
self.bounds = node.state
def branch(self):
L, U = self.bounds
mid = 0.5 * (L + U)
for l,u in [(L,mid), (mid,U)]:
child = pybnb.Node()
child.state = (l,u)
yield child
Write a solve script:
# solve_simple.py
import simple
problem = simple.Simple()
results = pybnb.solve(problem,
absolute_gap=1e-9)
Run the script:
$ mpirun -np 4 python solve_simple.py
Using non-default solver options:
- absolute_gap: 1e-09 (default: 0)
Starting branch & bound solve:
- dispatcher pid: 34902 (Ozymandias.local)
- worker processes: 3
---------------------------------------------------------------------------------------------------------------------------
Nodes | Objective Bounds | Work
Expl Unexpl | Incumbent Bound Rel. Gap Abs. Gap | Time (s) Nodes/Sec Imbalance Idle
0 1 | inf -inf inf% inf | 0.0 0.00 0.00% 0
* 1 2 | 1 -1 200.0000000% 2 | 0.0 1226.99 300.00% 1
* 2 3 | 0.5 -1 150.0000000% 1.5 | 0.0 2966.04 150.00% 0
* 4 5 | 0.25 -0.25 50.0000000% 0.5 | 0.0 8081.95 75.00% 0
* 8 9 | 0.125 -0.0625 18.7500000% 0.1875 | 0.0 12566.90 37.50% 0
Expl Unexpl | Incumbent Bound Rel. Gap Abs. Gap | Time (s) Nodes/Sec Imbalance Idle
* 16 17 | 0.062 -0.015625 7.7625000% 0.077625 | 0.0 15352.74 18.75% 0
* 32 33 | 0.031 -0.00390625 3.4906250% 0.03490625 | 0.0 15981.49 18.75% 0
* 64 65 | 0.016 -0.0009765625 1.6976563% 0.0169765625 | 0.0 18740.68 18.75% 0
* 128 129 | 0.008 -0.0002441406 0.8244141% 0.008244140625 | 0.0 21573.51 11.72% 0
* 256 257 | 0.004 -6.103516e-05 0.4061035% 0.004061035156 | 0.0 22166.96 8.20% 0
Expl Unexpl | Incumbent Bound Rel. Gap Abs. Gap | Time (s) Nodes/Sec Imbalance Idle
* 512 513 | 0.002 -1.525879e-05 0.2015259% 0.002015258789 | 0.0 21177.00 5.86% 0
* 1024 1025 | 0.001 -3.814697e-06 0.1003815% 0.001003814697 | 0.1 19978.42 9.38% 0
* 2048 2049 | 0 -9.536743e-07 0.0000954% 9.536743164e-07 | 0.1 21606.45 5.42% 0
24029 24030 | 0 -1.490116e-08 0.0000015% 1.490116119e-08 | 1.1 21961.03 5.98% 0
46159 46160 | 0 -3.72529e-09 0.0000004% 3.725290298e-09 | 2.1 22120.75 5.73% 0
Expl Unexpl | Incumbent Bound Rel. Gap Abs. Gap | Time (s) Nodes/Sec Imbalance Idle
65537 65538 | 0 -9.313226e-10 0.0000001% 9.313225746e-10 | 3.0 22459.50 6.20% 0
---------------------------------------------------------------------------------------------------------------------------
Absolute optimality tolerance met
Optimal solution found!
solver results:
- solution_status: optimal
- termination_condition: optimality
- objective: 0
- bound: -9.313226e-10
- absolute_gap: 9.313226e-10
- relative_gap: 9.313226e-10
- nodes: 65537
- wall_time: 2.96 s
- best_node: Node(objective=0)
Number of Workers: 3
Load Imbalance: 6.20%
- min: 21355 (proc rank=3)
- max: 22710 (proc rank=1)
Average Worker Timing:
- queue: 80.78% [avg time: 109.6 us, count: 65537]
- load_state: 0.44% [avg time: 596.1 ns, count: 65537]
- bound: 0.59% [avg time: 796.1 ns, count: 65537]
- objective: 3.52% [avg time: 4.7 us, count: 65537]
- branch: 3.36% [avg time: 4.6 us, count: 65537]
- other: 11.31% [avg time: 15.3 us, count: 65537]
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