Seeking multiple solutions: An updated survey on niching methods and their applications
Multimodal optimization (MMO) aiming to locate multiple optimal (or near-optimal) solutions
in a single simulation run has practical relevance to problem solving across many fields …
in a single simulation run has practical relevance to problem solving across many fields …
Real-parameter evolutionary multimodal optimization—A survey of the state-of-the-art
Multimodal optimization amounts to finding multiple global and local optima (as opposed to
a single solution) of a function, so that the user can have a better knowledge about different …
a single solution) of a function, so that the user can have a better knowledge about different …
A survey on evolutionary computation for complex continuous optimization
Complex continuous optimization problems widely exist nowadays due to the fast
development of the economy and society. Moreover, the technologies like Internet of things …
development of the economy and society. Moreover, the technologies like Internet of things …
Automatic niching differential evolution with contour prediction approach for multimodal optimization problems
Niching techniques have been widely incorporated into evolutionary algorithms (EAs) for
solving multimodal optimization problems (MMOPs). However, most of the existing niching …
solving multimodal optimization problems (MMOPs). However, most of the existing niching …
Adaptive multimodal continuous ant colony optimization
Seeking multiple optima simultaneously, which multimodal optimization aims at, has
attracted increasing attention but remains challenging. Taking advantage of ant colony …
attracted increasing attention but remains challenging. Taking advantage of ant colony …
Dual-surrogate-assisted cooperative particle swarm optimization for expensive multimodal problems
X Ji, Y Zhang, D Gong, X Sun - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Various real-world applications can be classified as expensive multimodal optimization
problems. When surrogate-assisted evolutionary algorithms (SAEAs) are employed to tackle …
problems. When surrogate-assisted evolutionary algorithms (SAEAs) are employed to tackle …
A distance-based locally informed particle swarm model for multimodal optimization
Multimodal optimization amounts to finding multiple global and local optima (as opposed to
a single solution) of a function, so that the user can have a better knowledge about different …
a single solution) of a function, so that the user can have a better knowledge about different …
Differential evolution with neighborhood mutation for multimodal optimization
In this paper, a neighborhood mutation strategy is proposed and integrated with various
niching differential evolution (DE) algorithms to solve multimodal optimization problems …
niching differential evolution (DE) algorithms to solve multimodal optimization problems …
Distributed individuals for multiple peaks: A novel differential evolution for multimodal optimization problems
Locating more peaks and refining the solution accuracy on the found peaks are two
challenging issues in solving multimodal optimization problems (MMOPs). To deal with …
challenging issues in solving multimodal optimization problems (MMOPs). To deal with …
Multimodal estimation of distribution algorithms
Taking the advantage of estimation of distribution algorithms (EDAs) in preserving high
diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for …
diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for …