Multimodal optimization is characterized by the dual imperative of achieving global peak diversity and local precision enhancement for discovered solutions. An adaptive memetic differential evolution is proposed in this work based on the virtual popu...
The electronic control module is an important part of a digital electronic detonator, which undergoes a complex production process that includes three electrical performance tests and three visual inspection procedures. In each inspection procedure,...
To strengthen the population diversity and search capability of equilibrium optimizer (EO), a dynamic multi-population mutation architecture-based equilibrium optimizer (DMMAEO) is proposed. Firstly, a dynamic multi-population guidance mechanism is c...
Differential Evolution (DE) has been extensively adopted for multi-objective optimization due to its efficient and straightforward framework. In DE, the mutation operator influences the evolution of the population. In this paper, an adaptive Grid-bas...
Obtaining high convergence and uniform distributions remains a major challenge in most metaheuristic multi-objective optimization problems. In this article, a novel multi-objective particle swarm optimization (PSO) algorithm is proposed based on Gaus...
Due to the complexity of multi-objective engineering problems, solutions obtained by many algorithms often exhibit poor distribution, and the algorithms tend to fall into local optima. To effectively alleviate these issues, an improved multi-objectiv...
Particle swarm optimization (PSO) is one of the most popular, nature inspired optimization algorithms. The canonical PSO is easy to implement and converges fast, however, it suffers from premature convergence. The comprehensive learning particle swar...
In this work, we propose a new test case generation approach that can cover behavioural scenarios individually in a multi-agent system. The purpose is to identify, in the case of the detection of an error, the scenario that caused the detected error,...
In this research, a novel enhanced gravitational search algorithm (EGSA) is proposed to resolve the multi-objective optimization model, considering the power generation of a hydropower enterprise and the peak operation requirement of a power system....
Mine extraction planning has a far-reaching impact on the production management and overall economic efficiency of the mining enterprise. The traditional method of preparing underground mine production planning is complicated and tedious, and reachin...
Background: Precision oncology has been increasingly used in clinical practice and rapidly evolving in the oncology field. Thus, this study was performed to assess the frequency of germline mutations in early and late onset familial breast cancer (BC...
Cold rolling is the precision finishing stage in the steel production process, and its scheduling optimization is essential for enhancing production efficiency. To address the complex process constraints and objectives, this paper proposes a multi-gr...
A quick and effective way of segmenting images is the Otsu threshold method. However, the complexity of time grows exponentially as the number of thresolds rises. The aim of this study is to address the issues with the standard threshold image segmen...
Emergence of human immunodeficiency virus type 1 (HIV-1) drug resistance arises from mutation fixation in the viral genome during antiretroviral therapy. Primary mutations directly confer antiviral drug resistance, while secondary mutations arise tha...
Marine Predator Algorithm (MPA) is a meta-heuristic algorithm based on the foraging behavior of marine animals. It has the advantages of few parameters, simple setup, easy implementation, accurate calculation, and easy application. However, compared...
The intelligent manufacturing of power systems has led to many challenges. The cyber-physical system (CPS) was introduced to solve the problem of insufficient integration of equipment and systems. It brings advantages, but also risks. In the distribu...
Aiming at solving the problems of large calculation, time-consuming, and low segmentation accuracy of multi-threshold image segmentation, an adaptive threshold value based differential evolution algorithm is proposed in this paper. Firstly, an opposi...
The IDH somatic mutation status is an important basis for the diagnosis and classification of gliomas. We proposed a “6-Step” general radiomics model to noninvasively predict the IDH mutation status by simultaneously tuning combined multi...
Target assignment is a core issue in command and control, aiming to rationally distribute targets among multiple coordinated operational units based on battlefield conditions to maximize overall operational effectiveness. This study proposes a target...
In the context of carbon peaking and carbon neutralization, distributed photovoltaics is a relatively mature new energy power generation technology that is being widely promoted. However, the randomness and volatility of distributed generation bring...
Under the background of over-exploitation of groundwater and urban expansion, the land subsidence in the Beijing Plain has dramatically increased recently, and has demonstrated obvious mutation characteristics. Firstly, this paper used the land-use t...
Parkinson’s disease (PD) is typically sporadic; however, multi-incident families provide a powerful platform to discover novel genetic forms of disease. Their identification supports deciphering molecular processes leading to disease and may inform o...
The WHO classification since 2016 confirms the importance of integrating molecular diagnosis for prognosis and treatment decisions of adult-type diffuse gliomas. This motivates the development of non-invasive diagnostic methods, in particular MRI, to...
An edge-weighted consensus-based formation control strategy is presented for mobile robots. In the edge-weighted strategy, a desired formation pattern is achieved by adjusting gain weights related to the distance between robots. Moreover, the edge-we...
Mutations in the BRCA1 and BRCA2 genes are known risk factors and drivers of breast and ovarian cancers. So far, few studies have been focused on understanding the differences in transcriptome and functional landscapes associated with the disease (br...
Pancreatic Ductal adenocarcinoma (PDAC) is an aggressive cancer commonly exhibiting KRAS-activating mutations. Alcohol contributes to the risk of developing PDAC in humans, and murine models have shown alcohol consumption in the context of KRAS mutat...
By addressing the flexible job shop scheduling problem (FJSP), this paper proposes a new type of algorithm for the FJSP. We named it the hybrid coronavirus population immunity optimization algorithm. Based on the characteristics of the problem, first...
To solve the multi-objective optimization problem (MOP) for parameter optimization of a multiple spacecraft attitude controller, an improved multi-objective moth–flame optimization algorithm based on r-domination (rIMOMFO) is proposed. In rIMOM...
Somatic heterozygous mutations in the active site of the enhancer of zeste homolog 2 (EZH2) are prevalent in diffuse large B-cell lymphoma (DLBCL) and acute myeloid leukemia (AML). The methyltransferase activity of EZH2 towards lysine 27 on histone H...
Although the cost-reference particle filter (CRPF) has a good advantage in solving the state estimation problem with unknown noise statistical characteristics, its estimation accuracy is still affected by the lack of particle diversity and sensitivit...
Three-dimensional path planning in emergency logistics is a complex optimization problem, particularly challenging because it requires considering conflicting objectives such as flight time, energy consumption, and obstacle avoidance. Unlike most urb...
In the real word, optimization problems in multi-objective optimization (MOP) and dynamic optimization can be seen everywhere. During the last decade, among various swarm intelligence algorithms for multi-objective optimization problems, glowworm swa...
The optimal scheduling of multi-type combine harvesters is a crucial topic in improving the operating efficiency of combine harvesters. Due to the NP-hard property of this problem, developing appropriate optimization approaches is an intractable task...
A Multi-Agent Motion Prediction and Tracking method based on non-cooperative equilibrium (MPT-NCE) is proposed according to the fact that some multi-agent intelligent evolution methods, like the MADDPG, lack adaptability facing unfamiliar environment...
Background: Levofloxacin is a broad-spectrum third-generation fluoroquinolone with bactericidal activity against Streptococcus species. We aimed to investigate the susceptibility rates of levofloxacin, the genetic determinants contributing to resista...
Precision neurosurgery is rapidly evolving as a medical specialty by merging genomic medicine, multi-omics technologies, and artificial intelligence (AI) technology, while at the same time, society is shifting away from the traditional, anatomic mode...
This study proposes an improved multi-objective black-winged kite algorithm (MOBKA-QL) integrating Q-learning with adaptive mutation strategies for optimizing multi-objective scheduling in integrated energy systems (IES). The algorithm dynamically se...
Some problems exist in classical optimization algorithms to solve multi-modal optimization problems and other complex systems. A Dynamic Niches-based Improved Hybrid Breeding Optimization (DNIHBO) algorithm is proposed to address the multi-modal opti...
Next-generation sequencing (NGS) is the technology of choice for the routine screening of tumor samples in clinical practice. In this setting, the targeted sequencing of a restricted number of clinically relevant genes represents the most practical o...
In the past two decades, China’s manufacturing industry has achieved great success. However, pollution and environmental impacts have become more serious while this industry has grown. The economic and emission dispatch (EED) problem is a typical mul...
Next generation sequencing (NGS) allows parallel sequencing of multiple genes at a very high depth of coverage. The need to analyze a variety of targets for diagnostic/prognostic/predictive purposes requires multi-gene characterization. Multi-gene pa...
Amid the rapid growth of the new energy vehicle industry and the accelerating global shift toward green and low-carbon energy alternatives, this paper develops a multi-objective optimization model for an Electric Vehicle Integrated Energy Station (EV...
Currently, the multi-machine collaboration of agricultural machinery is one of the international frontiers and a topic of research interest in the field of agricultural equipment. However, the multi-machine cooperative operation of agricultural machi...
Integrated process planning and scheduling (IPPS) is important for modern manufacturing companies to achieve manufacturing efficiency and improve resource utilization. Meanwhile, multiple objectives need to be considered in the realistic decision-mak...
In the distribution field, distribution costs and customer service satisfaction are extremely important issues for enterprises. However, both the Vehicle Routing Problem with Soft Time Windows (VRPSTW) and the Vehicle Routing Problem with Fuzzy Time...
Meeting the growing demand for vegetable oil while promoting agricultural sustainability in Northeast China requires developing high-yield, high-oil-content soybean varieties. We present the comprehensive development and evaluation of Heinong 551, an...
We propose a computational framework for selecting biologically plausible genes identified by clustering of multi-omics data that reveal patients’ similarity, thus giving researchers a more comprehensive view on any given disease. We employ spe...
The application of 3D UAV path planning algorithms in smart cities and smart buildings can improve logistics efficiency, enhance emergency response capabilities as well as provide services such as indoor navigation, thus bringing more convenience and...
Lesch–Nyhan syndrome (LN) is an is an X-linked recessive inborn error of metabolism that arises from a deficiency of purine salvage enzyme hypoxanthine-guanine phosphoribosyltransferase (HPRT). The disease manifests severely, causing intellectu...
The African Vulture Optimization Algorithm (AVOA) is inspired by African vultures’ feeding and orienting behaviors. It comprises powerful operators while maintaining the balance of exploration and efficiency in solving optimization problems. To...
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