Foundational optimization algorithms are the core driving force behind deep learning, evolving from early stochastic gradient descent (SGD) to the widely adopted Adam family. However, as the scale of ...

If it feels like social platforms suddenly “get” you more than they used to, you’re not imagining it! In 2026, feeds aren’t only reacting to what you click anymore. They’re predicting what you ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...

Bio-inspired computational methods have gained popularity recently. These methods mimic the seemingly complex behavior of organisms to tackle difficult and often overwhelming problems. For example, ...

Researchers have developed a maximum power point tracking algorithm based on the social hierarchy and hunting strategy of grey wolves. When tested under realistic shading conditions, the grey wolf ...

Scientists in China have introduced developments to the RIME optimization method, which takes inspiration from the developmental course of hoarfrost in nature. They have compared it to other MPPT ...

The firefly algorithm is a bio-inspired metaheuristic grounded in the flashing behaviour of fireflies. In this model, candidate solutions are treated as fireflies whose brightness represents objective ...