⚡ Smart TSP Benchmark is a professional algorithm testing infrastructure with customizable scenarios and detailed metrics.
pip install smart-tsp-solverLaunch using Smart TSP Solver
pip install smart-tsp-solver
from smart_tsp_benchmark.tsp_benchmark import TSPBenchmark, AlgorithmConfig
from smart_tsp_solver import hierarchical_tsp_solver_v2
from smart_tsp_solver.algorithms.angular_radial.v1 import angular_radial_tsp_v1
from smart_tsp_solver.algorithms.angular_radial.v2 import angular_radial_tsp_v2
from smart_tsp_solver.algorithms.dynamic_gravity.v1 import dynamic_gravity_tsp_v1
from smart_tsp_solver.algorithms.dynamic_gravity.v2 import dynamic_gravity_tsp_v2
from smart_tsp_solver.algorithms.other.greedy.v2 import greedy_tsp_v2
def main():
config = {
'n_points': 100,
'seed': 123,
'point_generation': 'random',
'use_post_optimization': False,
'plot_results': True,
'verbose': True
}
benchmark = TSPBenchmark(config=config)
benchmark.add_algorithm(
name='Angular-radial v1',
config=AlgorithmConfig(
function=angular_radial_tsp_v1,
params={
"sort_by": "angle_distance",
"look_ahead": 100,
"max_2opt_iter": 100
},
post_optimize=True,
description="Angular-radial v1",
is_class=False
)
)
benchmark.add_algorithm(
name='Angular-radial v2',
config=AlgorithmConfig(
function=angular_radial_tsp_v2,
params={
"sort_by": "angle_distance",
"look_ahead": 100,
"max_2opt_iter": 100
},
post_optimize=True,
description="Angular-radial v2",
is_class=False
)
)
benchmark.add_algorithm(
name='Dynamic-gravity v1',
config=AlgorithmConfig(
function=dynamic_gravity_tsp_v1,
params={
"delta": 0.5,
"fast_2opt_iter": 100
},
post_optimize=True,
description="Dynamic-gravity v1",
is_class=False
)
)
benchmark.add_algorithm(
name='Dynamic-gravity v2',
config=AlgorithmConfig(
function=dynamic_gravity_tsp_v2,
params={
"delta": 0.5,
"fast_2opt_iter": 100
},
post_optimize=True,
description="Dynamic-gravity v2",
is_class=False
)
)
benchmark.add_algorithm(
name='Greedy v2',
config=AlgorithmConfig(
function=greedy_tsp_v2,
params={},
post_optimize=False,
description="Classic greedy TSP algorithm",
is_class=False,
)
)
benchmark.add_algorithm(
name='Hierarchical TSP',
config=AlgorithmConfig(
function=hierarchical_tsp_solver_v2,
params={
"cluster_size": 100,
"post_optimize": True
},
post_optimize=False,
description="Hierarchical clustering TSP solver",
is_class=False
)
)
benchmark.run_benchmark()
if __name__ == '__main__':
main()An example of testing TSP algorithms here
A.A. Suvorov
- Researcher specializing in computational optimization and high-performance algorithms
- Focused on bridging theoretical computer science with practical engineering applications
- This project represents extensive research into spatial optimization techniques
Explore other projects on GitHub.
This project is offered under a dual-licensing model.
This license is free of charge and allows you to use the software for:
- Personal and educational purposes
- Academic research and open-source projects
- Evaluation and testing
Important: Any use by a commercial organization or for commercial purposes (including internal development and prototyping) requires a commercial license.
A commercial license is required for:
- Integrating this software into proprietary products
- Using it in internal operations within a company
- SaaS and hosted services that incorporate this software
- Obtaining priority support and indemnification
To obtain a commercial license, please contact us directly at:
📧 smartlegiondev@gmail.com
For those interested in the theoretical foundations:
-
smart-tsp-solver - My Python library featuring advanced heuristics (
Dynamic Gravity,Angular Radial) for solving large TSP instances where finding the exact optimum is impractical. - Exact TSP Solutions (TSP ORACLE): exact-tsp-solver - Optimal solutions for small instances
- Spatial Optimization: Computational geometry approaches for large-scale problems
- Heuristic Analysis: Comparative study of modern TSP approaches
Visual analysis showing Angular-radial's optimal sector-based routing, Dynamic-gravity's smooth trajectories, Greedy's suboptimal clustering
==================================================
SMART TSP ALGORITHMS BENCHMARK
==================================================
Cities: 100
Seed: 123
Generation: cluster
Post-opt: OFF
Algorithms:
- Angular-radial v1: sort_by=angle_distance, look_ahead=1001, max_2opt_iter=1001
- Angular-radial v2: sort_by=angle_distance, look_ahead=1000, max_2opt_iter=1001
- Dynamic-gravity v1: delta=0.5, fast_2opt_iter=1001
- Dynamic-gravity v2: delta=0.5, fast_2opt_iter=1001
- Greedy v2: start_point=0
==================================================
==================================================
Running Angular-radial v1 algorithm...
Description: Angular-radial v1
Parameters: sort_by=angle_distance, look_ahead=1001, max_2opt_iter=1001
Completed in 0.0842 seconds
Route length: 553.66
==================================================
==================================================
Running Angular-radial v2 algorithm...
Description: Angular-radial v2
Parameters: sort_by=angle_distance, look_ahead=1000, max_2opt_iter=1001
Completed in 0.0088 seconds
Route length: 553.66
==================================================
==================================================
Running Dynamic-gravity v1 algorithm...
Description: Dynamic gravity v1
Parameters: delta=0.5, fast_2opt_iter=1001
Completed in 0.0075 seconds
Route length: 567.00
==================================================
==================================================
Running Dynamic-gravity v2 algorithm...
Description: Dynamic gravity v2
Parameters: delta=0.5, fast_2opt_iter=1001
Completed in 0.0073 seconds
Route length: 534.90
==================================================
==================================================
Running Greedy v2 algorithm...
Description: Classic greedy TSP algorithm
Parameters: start_point=0
Completed in 0.0016 seconds
Route length: 609.21
==================================================
==============================================================================================================================
DETAILED ALGORITHM COMPARISON
==============================================================================================================================
Algorithm | Time (s) | vs Best | Length | vs Best | Params
------------------------------------------------------------------------------------------------------------------------------
Greedy v2 | 0.0016 | BEST | 609.21 | +13.89% | start_point=0
Dynamic-gravity v2 | 0.0073 | +348.65% | 534.90 | BEST | delta=0.5, fast_2opt_iter=1001
Dynamic-gravity v1 | 0.0075 | +361.28% | 567.00 | +6.00% | delta=0.5, fast_2opt_iter=1001
Angular-radial v2 | 0.0088 | +441.26% | 553.66 | +3.51% | sort_by=angle_distance, look_ahead=1000, max_2opt_iter=1001
Angular-radial v1 | 0.0842 | +5064.72% | 553.66 | +3.51% | sort_by=angle_distance, look_ahead=1001, max_2opt_iter=1001
==============================================================================================================================
PERFORMANCE ANALYSIS:
- Fastest algorithm(s): Greedy v2 (0.0016 sec)
- Shortest route(s): Dynamic-gravity v2 (534.90 units)
==================================================
SMART TSP ALGORITHMS BENCHMARK
==================================================
Cities: 1001
Seed: 0
Generation: cluster
Post-opt: OFF
Algorithms:
- Angular-radial v1: sort_by=angle_distance, look_ahead=1001, max_2opt_iter=1001
- Angular-radial v2: sort_by=angle_distance, look_ahead=1000, max_2opt_iter=1001
- Dynamic-gravity v1: delta=0.5, fast_2opt_iter=1001
- Dynamic-gravity v2: delta=0.5, fast_2opt_iter=1001
- Greedy v2: start_point=0
==================================================
==================================================
Running Angular-radial v1 algorithm...
Description: Angular-radial v1
Parameters: sort_by=angle_distance, look_ahead=1001, max_2opt_iter=1001
Completed in 0.2531 seconds
Route length: 1388.82
==================================================
==================================================
Running Angular-radial v2 algorithm...
Description: Angular-radial v2
Parameters: sort_by=angle_distance, look_ahead=1000, max_2opt_iter=1001
Completed in 0.1263 seconds
Route length: 1388.82
==================================================
==================================================
Running Dynamic-gravity v1 algorithm...
Description: Dynamic gravity v1
Parameters: delta=0.5, fast_2opt_iter=1001
Completed in 0.0279 seconds
Route length: 1486.12
==================================================
==================================================
Running Dynamic-gravity v2 algorithm...
Description: Dynamic gravity v2
Parameters: delta=0.5, fast_2opt_iter=1001
Completed in 0.0248 seconds
Route length: 1485.03
==================================================
==================================================
Running Greedy v2 algorithm...
Description: Classic greedy TSP algorithm
Parameters: start_point=0
Completed in 0.0022 seconds
Route length: 1612.74
==================================================
================================================================================================================================
DETAILED ALGORITHM COMPARISON
================================================================================================================================
Algorithm | Time (s) | vs Best | Length | vs Best | Params
--------------------------------------------------------------------------------------------------------------------------------
Greedy v2 | 0.0022 | BEST | 1612.74 | +16.12% | start_point=0
Dynamic-gravity v2 | 0.0248 | +1016.15% | 1485.03 | +6.93% | delta=0.5, fast_2opt_iter=1001
Dynamic-gravity v1 | 0.0279 | +1156.99% | 1486.12 | +7.01% | delta=0.5, fast_2opt_iter=1001
Angular-radial v2 | 0.1263 | +5590.97% | 1388.82 | BEST | sort_by=angle_distance, look_ahead=1000, max_2opt_iter=1001
Angular-radial v1 | 0.2531 | +11304.79% | 1388.82 | BEST | sort_by=angle_distance, look_ahead=1001, max_2opt_iter=1001
================================================================================================================================
PERFORMANCE ANALYSIS:
- Fastest algorithm(s): Greedy v2 (0.0022 sec)
- Shortest route(s): Angular-radial v1, Angular-radial v2 (1388.82 units)
Disclaimer: Performance results shown are for clustered distributions. Results may vary based on spatial characteristics. Always evaluate algorithms on your specific problem domains.
