The increasing energy prices and pollutants from fossil fuels that threaten the climate, there
is a growing preference for renewable energy. The implementation of hybrid renewable …

Surrogate-assisted evolutionary algorithms (EAs) have been intensively used to solve
computationally expensive problems with some success. However, traditional EAs are not …

The escalating costs of electricity, coupled with the urgent environmental challenges posed
by fossil fuel consumption, underscore the necessity of transitioning to renewable energy …

This study presents an autoencoder-embedded optimization (AEO) algorithm which involves
a bi-population cooperative strategy for medium-scale expensive problems (MEPs). A huge …

Landslide susceptibility (LS) map** is an essential tool for landslide risk assessment. This
study aimed to provide a new approach with better performance for landslide map** and …

To address the growing global concern regarding increased wildfire occurrences and their
widespread socio-ecological impacts, cost-effective and practical approaches must be …

Large-scale multi-objective and many-objective problems are widely existing in the real-
world. These problems are extremely challenging to deal with as a result of exponentially …

Computational intelligence helps in detecting erroneous decisions and fastens the whole
process of decision making by applying various techniques. In this study, we will discuss the …

A multi-objective maintenance problem of a plaza building is presented using a dynamic
fuzzy maintenance scheduling model (DFMS). There are multiple component machines and …

大型复杂工程装备的优化设计通常为高复杂度, 高维度的优化问题, 即所谓的大规模黑箱优化
问题, 其特点是目标函数和/或约束函数解析式不可知且设计变量维度很高. **年来 …