This paper systematically covers the significant developments of the last decade, including
surrogate modeling of electrical machines and direct and stochastic search algorithms for …

This paper presents a state-of-the-art review of axial-flux permanent-magnet (AFPM)
machines in the aspects of construction, features, electromagnetic and thermal modeling …

Niching techniques have been widely incorporated into evolutionary algorithms (EAs) for
solving multimodal optimization problems (MMOPs). However, most of the existing niching …

Taking the advantage of estimation of distribution algorithms (EDAs) in preserving high
diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for …

Multimodal optimization problem (MMOP), which targets at searching for multiple optimal
solutions simultaneously, is one of the most challenging problems for optimization. There …

In practical situations, it is very often desirable to detect multiple optimally sustainable
solutions of an optimization problem. The population-based evolutionary multimodal …

Multimodal optimization problems (MMOPs) require the algorithms to find multiple global or
local optima in a single run, which is considered a difficult task. In recent years, niching …

In this paper, the recently developed method, so-called ray optimization, is employed for size
and shape optimization of truss structures. The goal function of the present optimization …

Multimodal optimization problems (MMOPs) require algorithms to locate multiple optima
simultaneously. When using evolutionary algorithms (EAs) to deal with MMOPs, an intuitive …

Multimodal optimization problems consists of multiple equal or comparable spatially
distributed solutions. Niching and clustering differential evolution (DE) techniques have …