2025年7月12日 · Non-convex Function Non-convex optimization poses significant challenges due to the presence of multiple local optima. Various optimization algorithms, such as genetic algorithms, …

2021年10月12日 · Local optimization involves finding the optimal solution for a specific region of the search space, or the global optima for problems with no local optima. Global optimization involves …

In this paper we analyse the effects of mutation and selection in overcoming local optima. Two different approaches are commonly used by most black box algorithms. One strategy is to rely on variation …

2024年2月1日 · SAHO is a recently developed surrogate-assisted hybrid optimization algorithm using a local RBF model for low- to high-dimensional expensive problems, in which TLBO and DE are …

2026年1月23日 · In the world of optimization, finding the best solution to complex problems can be challenging, especially when the solution space is vast and filled with local optima. One powerful …

2020年11月1日 · The LEO enables the proposed GBO to escape from local optima. The performance of the new algorithm was evaluated in two phases. 28 mathematical test functions were first used to …

2016年5月1日 · An extensive study was conducted on 29 mathematical benchmark functions to analyze exploration, exploitation, local optima avoidance, and convergence behavior of the proposed algorithm.

2026年3月5日 · They can find approximate solutions quickly when global optimization is computationally expensive. These algorithms are suitable for problems with complex, non-linear, or irregular objective …

The hippopotamus optimization algorithm (HO) is a novel metaheuristic algorithm that solves optimization problems by simulating the behavior of hippopotamuses. However, the traditional HO …

2020年3月5日 · Although these methods are efficient for problems with linear search spaces (unimodal), they are prone to local optima entrapment when applying to problems with non-linear search spaces, …