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Is your feature request related to a problem? Please describe.
I'm having a data of network and the optimization problems defined is to find best nodes in a graph. Each node relation can be defined using networkx. Each particle able to stay at nodes, and traveling between nodes using edges, with weight of each edges means distance between nodes. After some research, pyswarms support random topology, that might be used. The difference is that random seems connects all dotes while not all edges connected directly in graph network data (can be visited by multiple jump between nodes).
My question is, is there any example utilizing networkx data and pyswarms?
If not, does pyswarms might be able to be used in this kind of situations (should I use the random topology and works from there)?
Describe the solution you'd like
A dedicated site or repo to showcase various pyswarms implementation, for advanced use case. Complimentary with the use cases here
The text was updated successfully, but these errors were encountered:
Is your feature request related to a problem? Please describe.
I'm having a data of network and the optimization problems defined is to find best nodes in a graph. Each node relation can be defined using networkx. Each particle able to stay at nodes, and traveling between nodes using edges, with weight of each edges means distance between nodes. After some research, pyswarms support random topology, that might be used. The difference is that random seems connects all dotes while not all edges connected directly in graph network data (can be visited by multiple jump between nodes).
My question is, is there any example utilizing networkx data and pyswarms?
If not, does pyswarms might be able to be used in this kind of situations (should I use the random topology and works from there)?
Describe the solution you'd like
A dedicated site or repo to showcase various pyswarms implementation, for advanced use case. Complimentary with the use cases here
The text was updated successfully, but these errors were encountered: