July 2024
Intermediate to advanced
418 pages
10h 25m
English
This part focuses on enhancing the performance of genetic algorithms through advanced programming techniques, specifically concurrency and cloud computing. The first chapter introduces concurrency, especially multiprocessing, as a tool to improve genetic algorithm efficiency. The concept is illustrated by applying various multiprocessing methods to a CPU-intensive version of the One-Max problem, demonstrating significant performance gains. Building on this, the next chapter shifts to a client-server model, partitioning the genetic algorithm between asynchronous client operations and server-based fitness function computations. This model is then practically implemented using ...
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