Since ancient times, maritime transportation has played a very important role for the global trade and economy of many countries. The volumes of all major types of cargo, which are transported by vessels, has substantially increased in recent years....
The knacks of evolutionary and swarm computing paradigms have been exploited to solve complex engineering and applied science problems, including parameter estimation for nonlinear systems. The population-based computational heuristics applied for pa...
Quantum neural architecture search (QNAS) has emerged as a promising approach for automatically designing parameterized quantum circuits (PQCs) for near-term quantum machine learning tasks. However, quantum evolutionary algorithm (QEA)-based QNAS met...
In advanced transportation-management systems, variable speed limits are a crucial application. Deep reinforcement learning methods have been shown to have superior performance in many applications, as they are an effective approach to learning envir...
This study proposes EvoDeep-Quality, a closed-loop hybrid framework integrating deep learning-based perception with multi-objective evolutionary optimization for adaptive quality control in smart manufacturing. The architecture combines a CNN-LSTM ne...
Large-scale multi-objective optimization problems involve high-dimensional decision variables, vast search spaces, and conflicting objectives, which often lead to slow convergence, premature convergence, and poorly distributed solutions when conventi...
As an effective biological control agent, Propylea japonica (Coleoptera: Coccinellidae) preys on aphids, whiteflies, planthoppers, and small caterpillars, playing a crucial role in pest management within agro-ecological systems. However, the lack of...
Improving absolute accuracy in industrial manipulators remains difficult because rigid-body kinematic calibration cannot fully represent configuration-dependent non-geometric effects. Drawing inspiration from biological brain–body co-adaptation...
Digital twins (DTs) are increasingly used in controlled-environment agriculture to model microclimates and drive energy-efficient control. However, long-term drift and seasonal variability require continuous recalibration and controller retuning. We...
Genetic Algorithms (GAs) are pillars of evolutionary computing and one of the most well-known population-based metaheuristic optimisation techniques. They are widely used in engineering and applied optimisation problems for their capabilities in find...
Ensuring fairness in machine learning while maintaining predictive performance remains a fundamental challenge in data science. Most fairness-aware learning approaches rely on fixed penalty scalarization or static multi-objective formulations, which...
Constrained multi-objective optimization (CMOP) is especially difficult when the feasible region is very narrow. In this study, we introduce Integrated-CMOEA, a clear and structured framework that uses structure-aware seeding, a projection-based repa...
SPARQ is an advanced global optimization algorithm, the direct evolution of an earlier method called ARQ2. It searches efficiently for the best solution to problems where the space of options is too vast to check exhaustively, such as tuning antenna...
The integration of machine learning with metaheuristic optimization has emerged as one of the most promising frontiers in artificial intelligence and global search. Metaheuristics offer flexibility and effectiveness in solving complex optimization pr...
Multi-threshold image segmentation is an important research topic in the fields of computer vision and image processing. Its core objective is to efficiently determine the optimal threshold combination within a high-dimensional and complex search spa...
The field of evolutionary multitasking optimization (EMTO) has been a highly anticipated research topic in recent years. EMTO aims to utilize evolutionary algorithms to concurrently solve complex problems involving multiple tasks. Despite considerabl...
The majority of non-linear systems nowadays are controlled online using rapid PI-controllers with linear characteristics. Evolutionary algorithms are rarely used, especially for online adaptive control, due to their time complexity. This paper propos...
Parameter calibration is critical for self-localization based on dead reckoning in the control of intelligent vehicles such as autonomous driving. Most traditional calibration methods for robotics control based on dead reckoning rely on data collecti...
Adaptive thermogenesis comprises shivering thermogenesis dependent on skeletal muscles and non-shivering thermogenesis (NST) mediated by uncoupling protein 1 (UCP1). Although the thermogenic function of UCP1 was adopted early in some placental mammal...
Adaptive changes encompass physiological, morphological, or behavioral modifications occurring in organisms in response to specific environmental conditions. These modifications may become established within a population through natural selection. Wh...
Formation control is one of the most concerning topics within the realm of swarm intelligence. This paper presents a metaheuristic approach that leverages a natural co-evolutionary strategy to solve the formation control problem for a swarm of missil...
This work proposes the use of a specialized algorithm based on evolutionary computation to the global MPPT regulation of panel of thermoelectric modules connected serially in numerous string sections. Each section of the thermovoltaic panel is equipp...
Metastatic breast cancer (MBC) remains incurable because of tumor evolution. Despite advances in targeted therapies—CDK4/6 inhibitors, PIK3 inhibitors, HER2-directed agents, and antibody–drug conjugates—median overall survival is mo...
The evolution and the emergence of new mutations of viruses affect their transmissibility and/or pathogenicity features, depending on different evolutionary scenarios of virus adaptation to the host. A typical trade-off scenario of SARS-CoV-2 evoluti...
We consider the problem of evolutionary self-organization of control strategies using the example of speculative trading in a non-stationary immersion market environment. The main issue that obstructs obtaining real profit is the extremely high insta...
In this paper, a novel hardware architecture for neuroevolution is presented, aiming to enable the continuous adaptation of systems working in dynamic environments, by including the training stage intrinsically in the computing edge. It is based on t...
Supply chain control requires balancing operational performance and financial efficiency when decisions are made using delayed and imperfect demand information. Although fixed heuristics, adaptive policies, and reinforcement learning approaches have...
As key components of the niche, ecological factors serve as critical parameters for characterizing the dynamic changes in the quality of ecological environments and determining the equilibrium state of ecosystems. Organisms within an ecosystem genera...
This paper proposes a dynamic adaptation of the crossover parameter (CR) in Differential Evolution (DE) using Type-3 fuzzy logic. The strategy involves adjusting the CR value according to the progress of the algorithm by employing a Type-3 fuzzy syst...
This study addresses the challenges of real-time performance, safety, and trajectory smoothness in robot navigation by proposing an innovative variable-horizon model predictive control (MPC) scheme that utilizes evolutionary algorithms. To effectivel...
Phenylalanine ammonia-lyase (PAL) is the core branch-point enzyme connecting plant primary aromatic amino acid metabolism to the phenylpropanoid pathway, which determines carbon flux redistribution between growth and defense and is essential for plan...
Accurate state estimation is essential for the performance of uncalibrated visual servoing systems, yet it is frequently undermined by non-Gaussian disturbances—such as impulse noise, motion blur, and occlusions—whose heavy-tailed statist...
Unstable technological processes, such as turbulent gas and hydrodynamic flows, generate time series that deviate sharply from the assumptions of classical statistical forecasting. These signals are shaped by stochastic chaos, characterized by weak i...
In studies of intelligent agents, the pursuit–evasion problem, commonly related to the predator–prey paradigm, has been used as a reference setting for examining decision-making, coordination, and adaptation in multi-agent systems. In thi...
Enhancing Evolutionary Algorithms (EAs) using mathematical elements significantly contribute to their development and control the randomness they are experiencing. Moreover, the automation of the primary process steps of EAs is still one of the harde...
The facility layout problem is one of the fundamental production system management problems. It has a significant impact on overall system efficiency. This paper introduces a new facility layout problem that allows for choosing from multiple variants...
Arylalkylamine N-acetyltransferase (AANAT) is a crucial rate-limiting enzyme in the synthesis of melatonin. AANAT has been confirmed to be independently duplicated and inactivated in different animal taxa in order to adapt to the environment. However...
The accelerating digital transformation necessitates a paradigm shift in manufacturing, requiring a structured transition from traditional to smart manufacturing. To address the challenges of fragmented integration, this study proposes an evolutionar...
The issue of exploration-exploitation remains one of the most challenging tasks within the framework of evolutionary algorithms. To effectively balance the exploration and exploitation in the search space, this paper proposes a modified cloud particl...
The PID (proportional–integral–derivative) controller is the most widely used control method in modern engineering control because it has the characteristics of a simple algorithm structure and easy implementation. The traditional PID controller, in...
This paper presents a genetic-based control scheme that not only utilizes evolutionary characteristics to find the signal acquisition parameters, but also employs an adaptive scheme to control the search space and avoid the genetic control converging...
Collaborative robots (cobots) play a crucial role in modern industry by ensuring safe and efficient human–robot interaction. However, traditional control methods struggle with uncertainty handling and adaptability to dynamic environments. This...
Phage therapy, long overshadowed by antibiotics in Western medicine, has a well-established history in some Eastern European countries and is now being revitalized as a promising strategy against antimicrobial resistance (AMR). This resurgence of pha...
The most important characteristics of autonomous vehicles are their safety and their ability to adapt to various traffic situations and road conditions. In our research, we focused on the development of controllers for automated steering of a realist...
Background/Objectives: Mitochondrial genomes are widely used in phylogenetics and evolutionary and ecological research. Methods: In this study, the newest mitochondrial genome of Chelonoidis vicina was assembled and annotated. The comparative mitocho...
In the platform gravimeter, the stabilization accuracy of the gravimetric stabilization platform is crucial to improve the accuracy of gravity value measurements due to its uncertainties, such as mechanical friction, inter-device coupling interferenc...
(1) Background: Oxygen has exerted a great effect in shaping the environment and driving biological diversity in Earth’s history. Green lineage has evolved primary and secondary carotenoid biosynthetic systems to adapt to Earth’s oxygenat...
Malaria persists as a paradigmatic model of co-evolutionary complexity, emerging from the dynamic interplay among a human host, Anopheles vectors, and Plasmodium falciparum parasites. In human populations, centuries of selective pressures have sculpt...
The Gobiidae family occupy one of the most diverse habitat ranges of all fishes. One key reason for their successful colonization of different habitats is their ability to adapt to different energy demands. This energy requirement is related to the a...
Novel H7N9 influenza virus transmitted from birds to human and, since March 2013, it has caused five epidemic waves in China. Although the evolution of H7N9 viruses has been investigated, the evolutionary changes associated with codon usage are still...
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