April 2025
Intermediate to advanced
430 pages
14h 52m
English
This chapter covers hybrid mathematical optimization techniques in artificial intelligence (AI) to overcome local minima and slow convergence. Hybrid methods improve performance and robustness by combining multiple optimization strategies. The chapter divides hybridization into serial, parallel, and adaptive methods. Serial hybridization uses genetic algorithms (GA) for broad exploration and gradient descent for fine-tuning. Multiple algorithms run simultaneously in parallel hybridization, improving search diversity and robustness. Problem characteristics drive adaptive hybridization strategy adjustments. GA with gradient descent ...
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