Detecting community structures helps to reveal the functional units of complex networks. In this paper, the community detection problem is regarded as a modularity-based multi-objective optimization problem (MOP), and a parallel conical area communit...
A smart grid is a promising use-case of AIoT (AI (artificial intelligence) across IoT (internet of things)) that enables bidirectional communication among utilities that arises with demand response (DR) schemes for demand-side management (DSM) and co...
Existing evolutionary approaches to QRS detection are confined to the parametric tuning of rigid, human-designed pipelines or black-box neural architecture searches. This work applies evolutionary methods for the synthesis of QRS detection algorithms...
Parallel optimization enables faster and more efficient problem-solving by reducing computational resource consumption and time. By simultaneously combining multiple methods, such as evolutionary algorithms and swarm-based optimization, effective exp...
K-Means is a “de facto” standard clustering algorithm due to its simplicity and efficiency. K-Means, though, strongly depends on the initialization of the centroids (seeding method) and often gets stuck in a local sub-optimal solution. K-...
Well placement optimization is one of the most important means to control the decline of oilfields and improve the recovery rate in the development process of deep and heterogeneous reservoirs, such as deep buried carbonate oil reservoirs. However, t...
Parallel evolution usually occurs among related species with similar morphological characters in adaptation to particular environments. Four wild almond species (Prunus) sharing the character of dry mesocarp splitting are distributed in China, most o...
Today, although laser engraving technology is widely used in 2D image engraving, when the image is larger and more complicated, most existing algorithms for engraving path planning have a huge computational burden and reduced engraving efficiency. Ac...
This study focuses on a multi-objective heterogeneous parallel machine planning problem for industrial silicon smelting. Specifically, under the conflicting objectives of minimizing carbon emissions, rollover penalty costs, and load imbalance, the to...
Non-intrusive load monitoring (NILM) is a cost-effective approach that electrical appliances are identified from aggregated whole-field electrical signals, according to their extracted electrical characteristics, with no need to intrusively deploy sm...
The problem of wildfire spread prediction presents a high degree of complexity due in large part to the limitations for providing accurate input parameters in real time (e.g., wind speed, temperature, moisture of the soil, etc.). This uncertainty in...
A novel bare-bones particle swarm optimization (BBPSO) algorithm is proposed to realize intelligent mine ventilation decision-making and overcome the problems of low precision, low speed, and difficulty in converging on an optimal global solution. Th...
The topic of efficiently finding the global minimum of multidimensional functions is widely applicable to numerous problems in the modern world. Many algorithms have been proposed to address these problems, among which genetic algorithms and their va...
Recent advances in cloud computing, large language models, and deep learning have started a race to create massive High-Performance Computing (HPC) centers worldwide. These centers increase in energy consumption proportionally to their computing capa...
This paper introduces the hybrid population-based hill-climbing (HPHC) algorithm, a novel approach for generating cryptographically strong S-boxes that combines the efficiency of hill climbing with the exploration capabilities of population-based met...
Angiosperms include many taxa with dimorphic unisexual reproductive structures. These are well studied in some grasses, with maize as a key model, but other wind-pollinated lineages in Poales remain less explored. Within Poales, the family Restionace...
Structural static testing is paramount for validating the structural integrity of critical aerospace components. However, conventional test rigs are often constrained to fixed loading axes and frequently induce parasitic torques. Accurate reproductio...
Bio-inspired optimization algorithms have become an effective class of techniques for addressing challenging continuous optimization problems. In this work, we introduce the Parallel Enzyme Action Optimization (PEAO) algorithm, a parallel bio-inspire...
The key advantage of smart meters over rotating-disc meters is their ability to transmit electric energy consumption data to power utilities’ remote data centers. Besides enabling the automated collection of consumers’ electric energy consumption dat...
This paper introduces a method for the distribution of any and all population-based metaheuristics. It improves on the naive approach, independent multiple runs, while adding negligible overhead. Existing methods that coordinate instances across a cl...
Evolutionary perspectives have generated many questions and some answers in the study of human health and disease. The field of evolutionary medicine, and related analytics of evolutionary psychiatry and evolutionary psychology have extended and expa...
Global optimization is a widely used technique that finds application in many sciences such as physics, economics, medicine, etc., and with many extensions, for example, in the area of machine learning. However, in many cases, global minimization tec...
Bioengineering holds great promise to provide fast and efficient biocatalysts for methanol-based biotechnology, but necessitates proven methods to optimize physiology in engineered strains. Here, we highlight experimental evolution as an effective me...
Sequential object-oriented software remains difficult to parallelize because several important decisions are not entirely local. A useful decomposition should consider architectural structure, execution frequency, communication latency, and how much...
In this paper, we describe the concept of generative design approach applied to the automated evolutionary learning of mathematical models in a computationally efficient way. To formalize the problems of models’ design and co-design, the genera...
Households equipped with distributed energy resources, such as storage units and renewables, open the possibility of self-consumption of on-site generation, sell energy to the grid, or do both according to the context of operation. In this paper, a m...
The report considers the task of training a multilayer perceptron, formulated as a problem of multiobjective optimization under uncertainty. To solve this problem, the principle of vector minimax was used. A parallel software implementation of a hier...
In light of reducing train operation energy consumption while maintaining the passenger service level for creating sustainable urban rail transit systems, we address a non-parallel train timetabling problem considering regenerative braking energy uti...
This paper presents an efficient algorithm for the reconfiguration of a parallel kinematic manipulator with four degrees of freedom. The reconfiguration of the parallel manipulator is posed as a nonlinear optimization problem where the design variabl...
Planning tasks are important in construction, manufacturing, logistics, and education. At the same time, scheduling problems belong to the class of NP-hard optimization problems. Ant colony algorithm optimization is one of the most common swarm intel...
Recently, the multiobjective evolutionary algorithms (MOEAs) have been designed to cope with the sparse unmixing problem. Due to the excellent performance of MOEAs in solving the NP hard optimization problems, they have also achieved good results for...
Feature selection in classification is a complex optimization problem that cannot be solved in polynomial time. Bi-objective feature selection, aiming to minimize both selected features and classification errors, is challenging due to the conflict be...
Background: Abiogenesis is hypothesized to have occurred in the aquatic environments of the early Earth approximately 3.8–4.0 billion years ago, in oceans containing high concentrations of ions (Na+ ≈ 470 mmol/L, Cl− ≈ 545 mmo...
In this paper, we investigate the problem of optimal control of complex multistage chemical reactions, which is considered a nonlinear global constrained optimization problem. This class of problems is computationally expensive due to the inclusion o...
The evolution of complex multicellularity in land plants represents a pivotal event in the history of life on Earth, characterized by significant increases in biological complexity. This transition, classified as a Major Evolutionary Transition (MET)...
Metadata has been around and has evolved for centuries, albeit not recognized as such. Medieval manuscripts typically had illuminations at the start of each chapter, being both a kind of signature for the author writing the script and a pictorial cha...
Analysis of pathogen genome data sequenced from clinical and historical samples has made it possible to perform phylogenetic analyses of sexually transmitted infections on a global scale, and to estimate the diversity, distribution, and coevolutionar...
To address the issues of coarse-grained thread allocation and difficult load balancing in compiler automatic parallelization for processors, this paper proposes a loop-block-level automatic parallelization method for compilers based on an iterative c...
Quantifying viral growth rates is key to understanding evolutionary dynamics and the potential for mutants to escape antiviral drugs. Defining evolutionary escape paths and their impact on viral fitness allows for the development of drugs that are re...
This paper generalizes the iterated greedy algorithm to solve a multi-objective facility location problem known as the Bi-objective p-Center and p-Dispersion problem (
Machine learning algorithms are used in many applications nowadays. Sometimes, we need to describe how the decision models created output, and this may not be an easy task. Information visualization (InfoVis) techniques (e.g., TreeMap, parallel coord...
Large-scale constrained multi-objective optimization problems (LCMOPs) pose significant challenges due to the curse of dimensionality, complex constraint landscapes, and high computational overhead. In time-sensitive scenarios, existing large-scale c...
Facility layout problem (FLP) is one of the hottest research areas in industrial engineering. A good facility layout can achieve efficient production management, improve production efficiency, and create high economic values. Because FLP is an NP-har...
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...
In Africa, hares (Lepus spp.) show a high variability in external phenotypes. Species identification, delimitation, and distinction are difficult, due to the generally shallow evolutionary divergence of species, high intraspecific phenotypic variabil...
Multiple sequence alignment (MSA) stands as a critical tool for understanding the evolutionary and functional relationships among biological sequences. Obtaining an exact solution for MSA, termed exact-MSA, is a significant challenge due to the combi...
As form follows function, pedal anatomy is embedded in a history of evolution. This literature review seeks to further the understanding of physiologic and pathologic flatfoot through cross-disciplinary research of expired and extant members of the H...
Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application in unsupervised, complex multidimensional problems that cannot be solved using traditi...
To maintain its development, the growing fetus is directly dependent on the placenta, an organ that acts as both a modulator and mediator. As an essential component of pregnancy that is derived from both maternal and fetal tissues, the placenta facil...
The evolution of protein-coding genes has both structural and regulatory components. The first can be assessed by measuring the ratio of non-synonymous to synonymous nucleotide substitutions. The second component can be measured as the normalized pro...
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