Algorithms, Volume 16, Issue 8

Industrial projects are plagued by uncertainties, often resulting in both time and cost overruns. This research introduces an innovative approach, employing Reinforcement Learning (RL), to address three distinct project management challenges within a...

The Bundle Enrichment Method (BEM-DC) is introduced for solving nonsmooth difference of convex (DC) programming problems. The novelty of the method consists of the dynamic management of the bundle. More specifically, a DC model, being the difference...

This work presents a comprehensive comparative analysis of four prominent swarm intelligence (SI) optimization algorithms: Ant Lion Optimizer (ALO), Bat Algorithm (BA), Grey Wolf Optimizer (GWO), and Moth Flame Optimization (MFO). When compared under...

Recently, a hypothesis providing a detailed equation for the Plantower CF_1 algorithm for PM_2.5 has been published. The hypothesis was originally validated using eight independent Plantower sensors in four PurpleAir PA-II monitors providing PM_2.5 est...

In this article, we analyze the spread of information on social media (Twitter) and purpose a strategy based on epidemiological models. It is well known that social media represent a strong tool to spread news and, in particular, fake news, due to th...

Modeling the spread of infections in networks is a well-studied and important field of research. Most infection and diffusion models require a real value or probability at the edges of the network as an input, but this is rarely available in real-lif...

This paper deals with systematic approaches for the analysis of stability properties and controller design for nonlinear dynamical systems. Numerical methods based on sum-of-squares decomposition or algebraic methods based on quantifier elimination a...

This article is devoted to the problem of determining the rational amount of spare parts in the warehouse of a service center of an automobile manufacturer’s branded network used for maintenance and current repairs. This problem was solved on t...

In this study, we propose a population-based, data-driven intelligent controller that leverages neural-network-based digital twins for hypothesis testing. Initially, a diverse set of control laws is generated using genetic programming with the digita...

Manufacturing companies face a significant challenge when developing their master production schedule, navigating unforeseen disruptions during daily operations. Moreover, fluctuations in demand pose a substantial risk to scheduling and are the main...

This paper presents a novel approach utilizing uniform rectangular arrays to design a constant-beamwidth (CB) linearly constrained minimum variance (LCMV) beamformer, which also improves white noise gain and directivity. By employing a generalization...

Reinforcement learning has been used on a variety of control tasks for drones, including, in previous work at the University of Bristol, on perching manoeuvres with sweep-wing aircraft. In this paper, a new aircraft model is presented representing fl...

Fast and efficient algorithms optimized for high performance computers are crucial for the real-time analysis of data in heavy-ion physics experiments. Furthermore, the application of neural networks and other machine learning techniques has become m...

In the field of Artificial Intelligence (AI) and Machine Learning (ML), a common objective is the approximation of unknown target functions $y=f\left(\mathbf{x}\right)$ using limited instances $S=({\mathbf{x}}^{\left(\mathbf{i}\right)},y^{\left(i\right)})$, where ${\mathbf{x}}^{\left(\mathbf{i}\right)}\in D$ and D represents the domain of interest. We re...

Vehicular Ad Hoc Network (VANETs) need methods to control traffic caused by a high volume of traffic during day and night, the interaction of vehicles, and pedestrians, vehicle collisions, increasing travel delays, and energy issues. Routing is one o...

One of the primary objectives of truss structure design optimization is to minimize the total weight by determining the optimal sizes of the truss members while ensuring structural stability and integrity against external loads. Trusses consist of pi...

Hub-and-Spoke (H&S) network modeling is a form of transport topology optimization in which network joins are connected through intermediate hub nodes. The Short Sea Shipping (SSS) problem aims to efficiently disperse passenger flows involving mul...

The rapid advancements in technology have given rise to groundbreaking solutions and practical applications in the field of the Industrial Internet of Things (IIoT). These advancements have had a profound impact on the structures of numerous industri...

Alzheimer’s disease is a chronic neurodegenerative disease that causes brain cells to degenerate, resulting in decreased physical and mental abilities and, in severe cases, permanent memory loss. It is considered as the most common and fatal fo...

Partial shading conditions lead to power mismatches among photovoltaic (PV) panels, resulting in the generation of multiple peak power points on the P-V curve. At this point, conventional MPPT algorithms fail to operate effectively. This research wor...

The standard photometric stereo model makes several assumptions that are rarely verified in experimental datasets. In particular, the observed object should behave as a Lambertian reflector, and the light sources should be positioned at an infinite d...

This paper focuses on the joint estimation of parameters and time delays for multi-input systems that contain unknown input delays and colored noise. A greedy pursuit hierarchical iteration algorithm is proposed, which can reduce the estimation cost....

Electric and autonomous aircraft (EAA) are set to disrupt current cargo-shipping models. To maximize the benefits of this technology, investors and logistics managers need information on target commodities, service location establishment, and the dis...

The Transportation Problem (TP) is a special type of linear programming problem, where the objective is to minimize the cost of distributing a product from a number of sources to a number of destinations. Many methods for solving the TP have been stu...

This study presents hybrid particle swarm optimization with quasi-Newton (HPSO-QN), a hybrid optimization method for accurately identifying mechanical parameters in two-mass model (2MM) systems. These systems are commonly used to model and control hi...

Complex natural resonances (CNRs) extraction methods such as matrix pencil method (MPM), Cauchy, vector-fitting Cauchy method (VCM), or Prony’s method decompose a signal in terms of frequency components and damping factors based on Baum’s...

The recognition of human activities using vision-based techniques has become a crucial research field in video analytics. Over the last decade, there have been numerous advancements in deep learning algorithms aimed at accurately detecting complex hu...

This Special Issue of the open access journal Algorithms is dedicated to showcasing cutting-edge research in algorithms for feature selection [...]

Bees, like other insects, indirectly contribute to job creation, food security, and poverty reduction. However, across many parts of the world, bee populations are in decline, affecting crop yields due to reduced pollination and ultimately impacting...

Security in the blockchain has become a topic of concern because of the recent developments in the field. One of the most common cyberattacks is the so-called phishing attack, wherein the attacker tricks the miner into adding a malicious block to the...

Grammatical Evolution is a Genetic Programming variant which evolves problems in any arbitrary language that is BNF compliant. Since its inception, Grammatical Evolution has been used to solve real-world problems in different domains such as bio-info...

In this paper, an algorithm for Mathematica is proposed for the computation of the asymptotic Fisher information matrix for a multivariate time series, more precisely for a controlled vector autoregressive moving average stationary process, or VARMAX...

The purpose of this study is to show how machine learning can be leveraged as a tool to govern social impact and drive fair and equitable investments. Many organizations today are establishing financial inclusion goals to promote social impact and ha...

The increasing popularity of cruise tourism has led to the need for effective planning and management strategies to enhance the city tour experience for cruise passengers. This paper presents a deep reinforcement learning (DRL)-based planner specific...

Hand gestures are an essential part of human-to-human communication and interaction and, therefore, of technical applications. The aim is increasingly to achieve interaction between humans and computers that is as natural as possible, for example, by...

Freight forwarding and transportation are the backbone of the modern economy. There are thousands of transportation companies on the market whose sole purpose is to deliver ordered goods from pickup to delivery. Transportation can be carried out by t...

An algorithm is presented for the construction of an asymptotic approximation of a stable stationary solution to a diffusion equation system in a two-dimensional domain with a smooth boundary and a source function that is discontinuous along some smo...

A new random forest-based model for solving the Multiple Instance Learning problem under small tabular data, called the Soft Tree Ensemble Multiple Instance Learning, is proposed. A new type of soft decision trees is considered, which is similar to t...

The aim of this paper is to present a systematic literature review of the existing research, published between 2006 and 2023, in the field of artificial intelligence for management information systems. Of the 3946 studies that were considered by the...

This work is a short review of the state of the art aiming to contribute to the use, disclosure, and propagation of systems of linear inequalities in real life, teaching, and research. It shows that the algebraic structure of their solutions consists...