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Does anyone have any experience with using OpenCV's AI capabilities to solve the Traveling Salesman Problem?

There is a Kaggle contest called Traveling Santa 2018 - Prime Paths (https://www.kaggle.com/c/traveling-santa-2018-prime-paths), and I'm going to enter into it.

I have an algorithm that should work, and once I finish the code, I'll put it into the public domain. That way anyone can use the code to enter into the contest. I'm not in it for the money. But again, does anyone have any experience using OpenCV's AI to solve the Traveling Salesman Problem?

Does anyone have any experience with using OpenCV's AI capabilities to solve the Traveling Salesman Problem?

There is a Kaggle contest called Traveling Santa 2018 - Prime Paths (https://www.kaggle.com/c/traveling-santa-2018-prime-paths), and I'm going to enter into it.

I have an algorithm that should work, and once I finish the code, I'll put it into the public domain. That way anyone can use the code to enter into the contest. I'm not in it for the money. But again, does anyone have any experience using OpenCV's AI to solve the Traveling Salesman Problem?

Does anyone have any experience with using OpenCV's AI capabilities to solve the Traveling Salesman Problem?

There is a Kaggle contest called Traveling Santa 2018 - Prime Paths (https://www.kaggle.com/c/traveling-santa-2018-prime-paths), and I'm going to enter into it.

I have an algorithm that should work, and once I finish the code, I'll put it into the public domain. That way anyone can use the code to enter into the contest. I'm not in it for the money. But again, does anyone have any experience using OpenCV's AI to solve the Traveling Salesman Problem?

Does anyone have any experience with using OpenCV's AI capabilities to solve the Traveling Salesman Problem?

There is a Kaggle contest called Traveling Santa 2018 - Prime Paths (https://www.kaggle.com/c/traveling-santa-2018-prime-paths), and I'm going to enter into it.

I have an algorithm that should work, and once I finish the code, I'll put it into the public domain. That way anyone can use the code to enter into the contest. I'm not in it for the money. But again, does anyone have any experience using OpenCV's AI to solve the Traveling Salesman Problem?

Does anyone have any experience with using OpenCV's AI capabilities to solve the Traveling Salesman Problem?

There is a Kaggle contest called Traveling Santa 2018 - Prime Paths (https://www.kaggle.com/c/traveling-santa-2018-prime-paths), and I'm going to enter into it.

I have an algorithm that should work, and once I finish the code, I'll put it into the public domain. That way anyone can use the code to enter into the contest. I'm not in it for the money. But again, does anyone have any experience using OpenCV's AI to solve the Traveling Salesman Problem?

The following image shows the federal capitols as 10-size black points, provincial capitols as 5-size black points, and the municipal capitals as 2-size black points.

The 1-size orange points are the remaining cities.

Does anyone have any experience with using OpenCV's AI capabilities to solve the Traveling Salesman Problem?

There is a Kaggle contest called Traveling Santa 2018 - Prime Paths (https://www.kaggle.com/c/traveling-santa-2018-prime-paths), and I'm going to enter into it.

I have an algorithm that should work, and once I finish the code, I'll put it into the public domain. That way anyone can use the code to enter into the contest. I'm not in it for the money. But again, does anyone have any experience using OpenCV's AI to solve the Traveling Salesman Problem?

The following image shows the federal capitols as 10-size black points, provincial capitols as 5-size black points, and the municipal capitals as 2-size black points.

The 1-size orange points are the remaining cities.

Does anyone have any experience with using OpenCV's AI capabilities to solve the Traveling Salesman Problem?

There is a Kaggle contest called Traveling Santa 2018 - Prime Paths (https://www.kaggle.com/c/traveling-santa-2018-prime-paths), and I'm going to enter into it.

I have an algorithm that should work, and once I finish the code, I'll put it into the public domain. That way anyone can use the code to enter into the contest. I'm not in it for the money. But again, does anyone have any experience using OpenCV's AI to solve the Traveling Salesman Problem?

The following image shows the federal capitols as 10-size black points, provincial capitols as 5-size black points, and the municipal capitals as 2-size black points.

The 1-size orange multicoloured points are the remaining cities.cities, broken down by country.

Does anyone have any experience with using OpenCV's AI capabilities to solve the Traveling Salesman Problem?

There is a Kaggle contest called Traveling Santa 2018 - Prime Paths (https://www.kaggle.com/c/traveling-santa-2018-prime-paths), and I'm going to enter into it.

I have an algorithm that should work, and once I finish the code, I'll put it into the public domain. That way anyone can use the code to enter into the contest. I'm not in it for the money. But again, does anyone have any experience using OpenCV's AI to solve the Traveling Salesman Problem?

The following image shows the federal capitols as 10-size black points, provincial capitols as 5-size black points, and the municipal capitals as 2-size black points.

The 1-size multicoloured points are the remaining cities, broken down by country.

Does anyone have any experience with using OpenCV's AI capabilities to solve the Traveling Salesman Problem?

There is a Kaggle contest called Traveling Santa 2018 - Prime Paths (https://www.kaggle.com/c/traveling-santa-2018-prime-paths), and I'm going to enter into it.

I have an algorithm that should work, and once I finish the code, I'll put it into the public domain. That way anyone can use the code to enter into the contest. I'm not in it for the money. But again, does anyone have any experience using OpenCV's AI to solve the Traveling Salesman Problem?

The following image shows the federal capitols as 10-size black points, provincial capitols as 5-size black points, and the municipal capitals as 2-size black points.

The 1-size multicoloured points are the remaining cities, broken down by country.

I am having trouble with my code. I am not certain that line 137 is correct (https://github.com/sjhalayka/hamiltonian_cycle_3/blob/3f765ad83e8e52634d4947272d72396ed5cd2bc9/hcycle.cpp#L137). Same with line 238 (https://github.com/sjhalayka/hamiltonian_cycle_3/blob/3f765ad83e8e52634d4947272d72396ed5cd2bc9/hcycle.cpp#L238). Can anyone help? Once I have this final step done, I will be able to make a normalized database that I can use to recursively find a solution to the TSP.TSP, with GA perhaps.

Does anyone have any experience with using OpenCV's AI capabilities to solve the Traveling Salesman Problem?

There is a Kaggle contest called Traveling Santa 2018 - Prime Paths (https://www.kaggle.com/c/traveling-santa-2018-prime-paths), and I'm going to enter into it.

I have an algorithm that should work, and once I finish the code, I'll put it into the public domain. That way anyone can use the code to enter into the contest. I'm not in it for the money. But again, does anyone have any experience using OpenCV's AI to solve the Traveling Salesman Problem?

The following image shows the federal capitols as 10-size black points, provincial capitols as 5-size black points, and the municipal capitals as 2-size black points.

The 1-size multicoloured points are the remaining cities, broken down by country.

I am having trouble with my code. I am not certain that line 137 is correct (https://github.com/sjhalayka/hamiltonian_cycle_3/blob/3f765ad83e8e52634d4947272d72396ed5cd2bc9/hcycle.cpp#L137). Same with line 238 (https://github.com/sjhalayka/hamiltonian_cycle_3/blob/3f765ad83e8e52634d4947272d72396ed5cd2bc9/hcycle.cpp#L238). Can anyone help? Once I have this final step done, I will be able to make a normalized database that I can use to recursively find a solution to the TSP, with GA perhaps.perhaps. Oh well, if I can't figure it out, I'll just do with countries and provinces alone, and just completely remove the municipality code.

Does anyone have any experience with using OpenCV's AI capabilities to solve the Traveling Salesman Problem?

There is a Kaggle contest called Traveling Santa 2018 - Prime Paths (https://www.kaggle.com/c/traveling-santa-2018-prime-paths), and I'm going to enter into it.

I have an algorithm that should work, and once I finish the code, I'll put it into the public domain. That way anyone can use the code to enter into the contest. I'm not in it for the money. But again, does anyone have any experience using OpenCV's AI to solve the Traveling Salesman Problem?

The following image shows the federal capitols as 10-size black points, provincial capitols as 5-size black points, and the municipal capitals as 2-size black points.

The 1-size multicoloured points are the remaining cities, broken down by country.

I am having trouble with my code. I am not certain that line 137 is correct (https://github.com/sjhalayka/hamiltonian_cycle_3/blob/3f765ad83e8e52634d4947272d72396ed5cd2bc9/hcycle.cpp#L137). Same with line 238 (https://github.com/sjhalayka/hamiltonian_cycle_3/blob/3f765ad83e8e52634d4947272d72396ed5cd2bc9/hcycle.cpp#L238). Can anyone help? Once I have this final step done, I will be able to make a normalized database that I can use to recursively find a solution to the TSP, with GA perhaps. Oh well, if I can't figure it out, I'll just do with countries and provinces alone, and just completely remove the municipality code.

Does anyone have any experience with using OpenCV's AI capabilities to solve the Traveling Salesman Problem?

There is a Kaggle contest called Traveling Santa 2018 - Prime Paths (https://www.kaggle.com/c/traveling-santa-2018-prime-paths), and I'm going to enter into it.

I have an algorithm that should work, and once I finish the code, I'll put it into the public domain. That way anyone can use the code to enter into the contest. I'm not in it for the money. But again, does anyone have any experience using OpenCV's AI to solve the Traveling Salesman Problem?

The following image shows the federal capitols as 10-size black points, provincial capitols as 5-size black points, and the municipal capitals as 2-size black points.

The 1-size multicoloured points are the remaining cities, broken down by country.

I am having trouble with my code. I am not certain that line 137 is correct (https://github.com/sjhalayka/hamiltonian_cycle_3/blob/3f765ad83e8e52634d4947272d72396ed5cd2bc9/hcycle.cpp#L137). Same with line 238 (https://github.com/sjhalayka/hamiltonian_cycle_3/blob/3f765ad83e8e52634d4947272d72396ed5cd2bc9/hcycle.cpp#L238). Can anyone help? Once I have this final step done, I will be able to make a normalized database that I can use to recursively find a solution to the TSP, with GA perhaps. Oh well, if I can't figure it out, I'll just do with countries and provinces alone, and just completely remove the municipality code.