Modern applications are increasingly built around networking, collaboration, and automation. Drones, or Unmanned Aerial Vehicles (UAVs), are a key part of this shift. Many complex missions require multiple UAVs to work together as a team, which means...
Wood–plastic composites (WPCs) have emerged as a sustainable and cost-effective material for construction, particularly in low-cost housing solutions. However, designing WPC panels that meet structural, serviceability, and manufacturing constra...
Heterogeneous quay cranes (HQCs) are the main energy-consuming equipment of automated container terminals, and they need to move from one bay to another along the rail and maintain a safe distance from one another. Improving the operational efficienc...
In the context of expensive constraint multi-objective problems, it is evident that the feasible domain shapes and sizes of different problems vary considerably. The difficulty in finding optimal solutions presents a significant challenge in ensuring...
Dynamic properties such as natural frequencies and mode shapes are directly affected by damage in structures. In this paper, changes in natural frequencies and mode shapes were used as the input to various objective functions for damage detection. Ob...
Wireless Sensor Networks (WSNs) are increasingly applied across various fields, but achieving effective three-dimensional terrain coverage in complex environments remains challenging due to signal obstruction and deployment optimization issues. This...
Power-electronics based converters are essential circuits in renewable energy applications such as electricity generated with photovoltaic panels. The research on the field is getting increasing attention due to climate change problems and their poss...
UAV mission planning is one of the core problems in the field of UAV applications. Currently, mission planning needs to simultaneously optimize multiple conflicting objectives and take into account multiple mutually coupled constraints, and tradition...
Evolutionary algorithms have been widely studied in the literature to find sub-optimal solutions to complex problems as the Traveling Salesman Problem (TSP). In such a problem, the target positions are usually static and punctually defined. The objec...
Binary zinc(II) oxide (ZnO) and copper(II) oxide (CuO) are used in a number of applications, including optoelectronic and semiconductor applications. However, no crystal structures have been reported for ternary Cu-Zn-O oxides. In that context, we in...
Multi-objective evolutionary optimization faces significant challenges due to guidance mismatch under complex Pareto-front geometries. This paper proposes a dynamic self-organizing map-assisted evolutionary algorithm (D-SOMA), a manifold-aware framew...
Production scheduling that involves distributed factories, machine maintenance, and resource constraints plays a crucial role in manufacturing. However, these realistic constraints have rarely been considered simultaneously in the hybrid flow shop (H...
Machining processes have been widely employed in the modern manufacturing industry to transform raw materials into final products, and they are of great importance in improving the environmental impact and production efficiency of this industry. The...
With the improvement of spectral resolution, the redundant information in the hyperspectral imaging (HSI) datasets brings computational, analytical, and storage complexities. Feature selection is a combinatorial optimization problem, which selects a...
Distributed hydrological models based on shallow water equations have gained popularity in recent years for the simulation of storm events, due to their robust and physically based routing of surface runoff through the whole catchment, including hill...
Integrated energy systems have become an important research topic in the pursuit of sustainable energy development. This paper examines regional integrated energy systems, presents the typical architecture of regional integrated energy systems, and b...
In this contribution, a novel methodology for multi-class classification in the field of Parkinson’s disease is proposed. The methodology is structured in two phases. In a first phase, the most relevant volumes of interest (VOI) of the brain ar...
Demand fluctuates in actual production. When manufacturers face demand under their maximum capacity, suspension shifts are crucial for cost reduction and on-time delivery. In this case, suspension shifts are needed to minimize idle time and prevent i...
This paper addresses a smoother fixed-time obstacle-avoidance trajectory planning based on double-stranded ribonucleic acid (dsRNA) splicing evolutionary algorithm for a dual-arm free-floating space robot, the smoothness of large joint angular veloci...
Thanks to their peculiar features, organic transistors are proving to be a valuable alternative to traditional semiconducting devices in several application fields; however, before releasing their exploitation, simulating their behaviour through adeq...
The combination and convergence of energy-intensive industries developed by ecological factors based on energy clusters is discussed in this paper. Here, a few models for the prediction of greenhouse effects are used as a single type of modeling. In...
The present research work introduces a novel mixture optimization methodology for biodiesel fuels using an Evolutionary Computation method inspired by biological evolution. Specifically, the optimal biodiesel composition is deduced from the applicati...
The hybrid flow shop scheduling problem (HFSP) with unrelated parallel machines (UPMs), sequence-dependent setup times (SDSTs), and inter-stage transportation times has recently emerged as a prominent research topic. To address this scheduling proble...
Car–trailer combinations can experience unstable motion modes such as trailer-sway, jackknifing and rollover that can lead to fatal accidents. These unstable motions can be mitigated with the use of an active trailer steering (ATS) system. Prio...
Due to the scarcity of conventional energy resources and the greenhouse effect, renewable energies have gained more attention. This paper proposes methods for multi-objective optimal design of hybrid renewable energy system (HRES) in both isolated-is...
Evolutionary algorithms have been widely used for tackling multi-objective optimization problems, while feature selection in classification can also be seen as a discrete bi-objective optimization problem that pursues minimizing both the classificati...
As one of the common methods to construct classifiers, naïve Bayes has become one of the most popular classification methods because of its solid theoretical basis, strong prior knowledge learning characteristics, unique knowledge expression forms, a...
The objective of optimal sensor placement in a dynamic system is to obtain a sensor layout that provides as much information as possible for structural health monitoring (SHM). Whereas most studies use only one modal assurance criterion for SHM, this...
Recent developments in lithium-ion batteries have improved their capacity, which allows them to be used in more applications like power tools. However, they also carry higher risks, such as thermal runaway, which can happen if they are damaged. To ma...
To address the challenges of combinatorial explosion and expensive evaluations in truck–drone (truck–UAV) collaborative delivery under complex geographical constraints, this paper proposes a Surrogate-assisted Rezone-Enhanced Multi-object...
In recent years, many constrained multi-objective evolutionary algorithms (CMOEAs) have primarily emphasized feasible solutions, overlooking the useful information contained in infeasible ones. This tendency effectively prioritizes feasibility over o...
Encouraging healthy and balanced diet plans is one of the most important action points for governments around the world. Generating healthy, balanced and inexpensive menu plans that fulfil all the recommendations given by nutritionists is a complex a...
The Quantitative Trait Loci (QTL) mapping problem aims to identify regions in the genome that are linked to phenotypic features of the developed organism that vary in degree. It is a principle step in determining targets for further genetic analysis...
The Dynamic Multi-objective Optimization Problem (DMOP) is one of the common problem types in academia and industry. The Dynamic Multi-Objective Evolutionary Algorithm (DMOEA) is an effective way for solving DMOPs. Despite the existence of many resea...
Accurate wind power generation prediction, which has positive implications for making full use of wind energy, seems still a critical issue and a huge challenge. In this paper, a novel hybrid approach has been proposed for wind power generation forec...
Random speckle structured light can increase the texture information of the object surface, so it is added in the binocular stereo vision system to solve the matching ambiguity problem caused by the surface with repetitive pattern or no texture. To i...
The assembly job shop is a prevalent production organization mode in manufacturing enterprises. During the processing and assembly of products, operation processing times are influenced by numerous factors, leading to significant uncertainty. This pa...
Most existing studies on the Shortest-Path Network Interdiction Problem (SPIP) adopt the attacker’s perspective, often overlooking the critical role of defender-oriented strategies. To support proactive defense, this paper introduces a novel pr...
To coordinate the economy, security and environment protection in the power system operation, a two-step many-objective optimal power flow (MaOPF) solution method is proposed. In step 1, it is the first time that knee point-driven evolutionary algori...
Data-driven evolutionary algorithms (DDEAs) are essential computational intelligent methods for solving expensive optimization problems (EOPs). The management of surrogate models for fitness predictions, particularly the selection and integration of...
Integrated optimization of well placement and hydraulic fracture parameters in naturally fractured shale gas reservoirs is of significance to enhance unconventional hydrocarbon energy resources in the oil and gas industry. However, the optimization t...
Optimizing hearing in patients with a unilateral cochlear implant (CI) and contralateral acoustic hearing is a challenge. Evolutionary algorithms (EA) can explore a large set of potential solutions in a stochastic manner to approach the optimum of a...
The precise prediction of the remaining useful life (RUL) of lithium-ion batteries is of great significance for improving energy management efficiency and extending battery lifespan, and it is widely applied in the fields of new energy and electric v...
Manual generation of test cases and scenario screening processes, during field architecture concept development, may produce a limited number of solutions that do not necessarily lead to an optimal concept selection. For more complex subsea field arc...
Health technology research brings together complementary interdisciplinary research skills in the development of innovative health technology applications. Recent research indicates that artificial intelligence can help achieve outstanding performanc...
With the rapid development of Industry 5.0, smart manufacturing has become a key focus in production systems. Hence, achieving efficient planning and scheduling on the shop floor is important, especially in job shop environments, which are widely enc...
Electric vehicle cell industry is an emerging area with fierce competition on technical innovation, in which the patent holder can choose different innovation diffusion options to maximize the return; however, the strategy is unclear in certain scena...
Overbounding the integrity risk is a significant challenge for Kalman filter (KF)-based advanced receiver autonomous integrity monitoring (ARAIM) when the measurement error has an uncertain time correlation. Thus, this paper presents a method that ad...
To address the issue of unbalanced path allocation in multi-UUV cooperative operations under inhomogeneous ocean environments during full-coverage search missions, this paper proposes a heterogeneous UUV path planning method that integrates a hybrid...
The mechanical parameters of surrounding rock are an essential basis for roadway excavation and support design. Aiming at the difficulty in obtaining the mechanical parameters of surrounding rock and large experimental errors, the optimized BP neural...
of 61