This article is a survey paper on solving spacecraft trajectory optimization problems. The
solving process is decomposed into four key steps of mathematical modeling of the problem …

Meta-heuristic algorithms are problem-solving methods which try to find good-enough
solutions to very hard optimization problems, at a reasonable computation time, where …

It has long been observed that for practically any computational problem that has been
intensely studied, different instances are best solved using different algorithms. This is …

This survey compiles ideas and recommendations from more than a dozen researchers with
different backgrounds and from different institutes around the world. Promoting best practice …

In this article, we build upon previous work on designing informative and efficient
Exploratory Landscape Analysis features for characterizing problems' landscapes and show …

Black-box optimization (BBO) has a broad range of applications, including automatic
machine learning, engineering, physics, and experimental design. However, it remains a …

This study introduces a novel method for identifying dynamic systems aimed at deriving
reduced-fractional-order models. Applicable to processes exhibiting an S-shaped step …

Classification is the key and most widely studied paradigm in machine learning community.
The selection of appropriate classification algorithm for a particular problem is a challenging …

Thirty years, 1993–2023, is a huge time frame in science. We address some major
developments in the field of evolutionary algorithms, with applications in parameter …

Photovoltaic (PV) systems play a significant role in power systems since they can convert
solar energy directly into electricity. Their conversion performance depends mainly on the …