The flexible job shop scheduling problem (FJSP) with transportation resources such as automated guided vehicles (AGVs) is prevalent in manufacturing enterprises. Multi-type AGVs are widely adopted to transfer jobs and realize the collaboration of dif...
The flight formation of unmanned aerial vehicles (UAVs) needs to be reconfigured whenever necessary to cope with complex environments and varying tasks. However, the continuity, nonlinearity and high dimensionality of the UAV formation control parame...
The generation of high-quality test cases remains challenging due to combinatorial explosion and difficulty balancing exploration-exploitation in complex parameter spaces. This paper presents a novel Hybrid Artificial Bee Colony (ABC) algorithm that...
Hinge joint damage is a typical form of damage occurring in simply supported slab bridges, which can present adverse effects on the overall force distribution of the structure. However, damage identification methods of hinge joint damage are still li...
In reservoir operation rule curves, it is necessary to apply rule curves to guide long-term reservoir management. This study proposes an approach to optimizing reservoir operation rule curves (RORCs) using intelligent optimization techniques from the...
In this study, the output characteristics of partial modules in a photovoltaic module array when subject to shading were first explored. Then, an improved particle swarm optimization (PSO) algorithm was applied to track the global maximum power point...
For the purpose of reducing noise from grain flow signal, this paper proposes a filtering method that is on the basis of empirical mode decomposition (EMD) and artificial bee colony (ABC) algorithm. At first, decomposing noise signal is performed ada...
Parameter estimation for fractional-order chaotic systems has been an interesting and important issue in theory and various fields of application. In this paper, fractional orders, as well as systematic parameters of fractional-order chaotic systems...
The efficiency and sustainability of a cellular manufacturing system (CMS) in batch type manufacturing is highly valued. This is done using a systematic method of equipment into machine cells, and components into part families, based on the suitable...
Due to the influence of unpredictable random events, the processing time of each operation should be treated as random variables if we aim at a robust production schedule. However, compared with the extensive research on the deterministic model, the...
A hybrid algorithm combining two metaheuristics is proposed to solve the flow-shop scheduling problem, aiming to minimise the makespan (Cmax). This approach accounts for random machine failures and limited buffer capacity between machines. Since flow...
The objective of this work is to present a Quick Gbest Guided artificial bee colony (ABC) learning algorithm to train the feedforward neural network (QGGABC-FFNN) model for the prediction of the trends in the stock markets. As it is quite important t...
Green manufacturing, which takes environmental effect and production benefit into consideration, has attracted increasing concern with the target of carbon peaking and carbon neutrality proposed. As a critical process in the manufacturing system, sho...
Passive power filters (PPFs) are most effective in mitigating harmonic pollution from power systems; however, the design of PPFs involves several objectives, which makes them a complex multiple-objective optimization problem. This study proposes a me...
It is well accepted that combined heat and power (CHP) generation can increase the efficiency of power and heat generation at the same time. With the increasing penetration of CHPs, determination of economic dispatch of power and heat becomes more co...
In order to meet the learning demands and challenges of the 21st century, computational thinking (CT) skills are important to start developing in early childhood education. The best way to cultivate CT skills, such as algorithmic thinking, is by impl...
The increasing incorporation of renewable energy sources, such as photovoltaic and wind power, results in considerable variability and uncertainty within modern power systems, thereby complicating load frequency control. Conventional controllers, inc...
With the application of finite element method on structure design and engineering analysis more and more widely, this paper presents a response surface model hybrid artificial bee colony method to optimize the thermal boundary conditions in finite el...
The Artificial Bee Colony (ABC) algorithm demonstrates strong exploration but converges slowly. To address this, AMRABC_Ts introduces an adaptive dimension modification rate mechanism with two search strategies. The exploration-favoured CABC strategy...
With the rapid development of internet technology, the amount of collected or generated data has increased exponentially. The sheer volume, complexity, and unbalanced nature of this data pose a challenge to the scientific community to extract meaning...
The rigid constraint of using heat in determining electricity for thermal power units is eliminated to improve the absorption capacity of wind power. In this study, heat storage devices and electric boilers are added to the cogeneration system to all...
Accurate forecasting of the energy demand is crucial for the rational formulation of energy policies for energy management. In this paper, a novel ensemble forecasting model based on the artificial bee colony (ABC) algorithm for the energy demand was...
This study addresses the route scheduling problem for the heterogeneous robotic delivery system (HRDS) that perform delivery tasks in an urban environment. The HRDS comprises two distinct types of vehicles: an unmanned ground vehicle (UGV), which is...
Land-use allocation is of great significance in urban development. This type of allocation is usually considered to be a complex multi-objective spatial optimization problem, whose optimized result is a set of Pareto-optimal solutions (Pareto front)...
Energy transition is an important factor when dealing with climate change and energy crisis under resource constraints. The performance evaluation of it is significant for improving and promoting the process of energy transition. This paper explores...
This paper focusses on a hybrid approach based on genetic algorithm (GA) and an adaptive neuro fuzzy inference system (ANFIS) for modeling the correlation between plasma arc cutting (PAC) parameters and the response characteristics of machined Monel...
Non-destructive estimation of the constituent properties of fruits and vegetables has led to a dramatic change in the agriculture and food industry, allowing accurate and efficient sorting of the products based on their internal properties. Therefore...
Facility location decisions directly affect operational costs, service quality, and customer allocation. However, minimising total cost may result in an imbalanced distribution of customers among open facilities, requiring both objectives to be consi...
A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students’ reading concentration rates and thus better in...
This article presents a microgrid that uses sustainable energy sources. It has a fuel cell (FC), wind energy production devices, and a superconducting magnetic energy storage (SMES) device. The performance of the suggested microgrid is improved by ad...
Although educational timetabling problems have been studied for decades, one instance of this, the school timetabling problem (STP), has not developed as quickly as examination timetabling and course timetabling problems due to its diversity and comp...
Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transi...
Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sens...
The mechanical characteristics of rock are greatly influenced by hydrochemical corrosion. The chemical corrosion impact and deformation properties of the meso-pore structure of rock under the action of different hydrochemical solutions for the stabil...
This study introduces a fuzzy logic-based two-degree-of-freedom PID (FL2DOF-PID) controller that is optimized using the Bee Algorithm (BA) to control the load frequency in a two-area linked power system that has both reheat thermal power plants and h...
The tooth flank distortion error occurring during the form-grinding (FG) of an involute helical gear can significantly compromise transmission performance. Conventional research approaches often focus on single-parameter optimization—either the...
The presence of abrasive particles in ceramic reinforced composite materials makes the machining complicated by generating friction at elevated temperatures. Lubricants can be used to prohibit the hazard of higher temperatures. This research work is...
High-voltage diodes, as key devices in power electronic systems, have important significance for system reliability and preventive maintenance in terms of storage life prediction. In this paper, we propose a hybrid modeling framework that integrates...
Ignition delay time (IDT) is a critical parameter for evaluating the autoignition characteristics of aviation fuels. However, its accurate prediction remains challenging due to the complex coupling of temperature, pressure, and compositional factors,...
An optimal mission assignment and path planning method of multiple unmanned aerial vehicles (UAVs) for disaster rescue is proposed. In this application, the UAVs include the drug delivery UAV, image collection UAV, and communication relay UAV. When i...
Groundwater is crucial for economic and agricultural development, particularly in arid areas where surface water resources are extremely scarce. The prediction of groundwater levels is essential for understanding groundwater dynamics and providing sc...
The frequent occurrence of extreme high-temperature events has significantly affected the operating characteristics and distributed photovoltaic (PV) hosting capacity of distribution networks. However, existing hosting capacity assessment methods rar...
Swarms of robots can use their sensing abilities to explore unknown environments and deploy on sites of interest. In this task, a large number of robots is more effective than a single unit because of their ability to quickly cover the area. However,...
This paper introduces a new optimization problem-solving method based on how the stingless bee Tetragonula carbonaria builds and regulates temperature in the hive. The Tetragonula carbonaria Optimization Algorithm (TGCOA) models three different behav...
This paper focuses on power system scheduling problems, aiming to enhance energy utilization efficiency through multi-energy complementarity. To support the “dual-carbon” strategic goals, this paper proposes a coordinated dispatch model f...
There are generally many redundant and irrelevant features in high-dimensional datasets, which leads to the decline of classification performance and the extension of execution time. To tackle this problem, feature selection techniques are used to sc...
This paper introduces a multi-objective discrete artificial bee colony (MODABC) algorithm, which aims to simultaneously minimize the makespan, total earliness and tardiness (ET), and total energy consumption (TEC) by efficiently scheduling a variety...
This paper introduces a comparison of training algorithms of radial basis function (RBF) neural networks for classification purposes. RBF networks provide effective solutions in many science and engineering fields. They are especially popular in the...
Based on the finite difference method and the artificial bee colony algorithm, the thermal conductivity in the two-dimensional unsteady-state heat transfer system is deduced. An improved artificial bee colony algorithm (IABCA), that artificial bee co...
Quantitative Structure–Activity Relationship (QSAR) aims to correlate molecular structure properties with corresponding bioactivity. Chance correlations and multicollinearity are two major problems often encountered when generating QSAR models. Featu...
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