Implementing a client-server model

Our plan is to divide the execution of the genetic algorithm into two distinct parts—client and server—outlined as follows:

• Client Component: The client will oversee the evolutionary logic in a centralized manner. This includes managing the initialization of populations, selection processes, and genetic operations such as crossover and mutation.
• Server Component: The server will be tasked with executing the resource-intensive fitness function calculations. It will employ multiprocessing to fully leverage its computational resources, circumventing the limitations imposed by Python’s Global Interpreter Lock (GIL).
• Client’s Use of Asynchronous I/O: Additionally, the client will employ asynchronous I/O, which operates on a single-threaded, event-driven model. This approach can efficiently handle I/O-bound tasks, allowing the program to concurrently manage other operations while waiting for I/O processes to complete...