January 1, 2025Journal of MechanicsOpen Access

Hybrid integration of genetic algorithm, artificial neural network and mathematical programming for optimization

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Modified hybrid optimization algorithm integrates genetic algorithms and neural networks to enhance solution accuracy for complex objectives.

The proposed hybrid optimization algorithm improves computational efficiency and solution accuracy for multi-objective optimization problems.
It successfully minimizes package warpage and adhesive peeling stress while maximizing contact stress in micro-joints.
This method uses finite element analysis to model complex behaviors, demonstrating effectiveness through experimental validation.
Different models within the algorithm are compared, showing significant improvements in optimization outcomes for ACF-based packages.

Cheng et al. (2025) studied this question.

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Modified hybrid optimization algorithm integrates genetic algorithms and neural networks to enhance solution accuracy for complex objectives.