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 ...

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 ...

The turbine-powered variant offers ten times the range of the original Grasshopper autonomous glider at a fraction of the cost of the manned platforms. DZYNE Technologies, the company that developed ...

Abstract: With the escalating intricacy of optimization tasks, conventional optimization techniques often struggle with drawbacks like getting ensnared in local minima and experiencing sluggish ...

Grasshopper Optimization Algorithms (GOAs) are a class of swarm-inspired metaheuristics modelled on the collective foraging behaviour of grasshopper swarms. Since its inception, GOA has been applied ...

An illustration of a magnifying glass. An illustration of a magnifying glass.

Abstract: In order to solve the problems of Grasshopper Optimization Algorithm (GOA) in the optimization process, such as easily falling into the local optimum and the slow convergence speed, a ...