With the development of electricity spot markets, the integrated renewable-storage plant (IRSP) has emerged as a crucial entity in real-time energy markets due to its flexible regulation capability. However, traditional methods face computational ine...
This study proposes a smart energy management framework for a university campus microgrid aimed at reducing dependence on the main power grid and increasing the utilization of photovoltaic (PV) generation under dynamic load and environmental conditio...
Buildings consume large amounts of energy resources and emit considerable amounts of greenhouse gases, especially existing buildings that do not meet energy standards. Building retrofitting is considered one of the most promising and significant solu...
Flow control flushing water from reservoirs has been imposed in South Korea for mitigating harmful cyanobacterial blooms (CyanoHABs) in rivers. This measure, however, can cause water shortage in reservoirs, as the measure adopting this flow control m...
Driver feedback signs (DFSs) are being adopted increasingly by municipalities around the world, as they have been proven to be a cost-effective countermeasure that improves road safety. However, research is still needed on developing a location-alloc...
Autonomous unmanned aerial vehicle (UAV) swarm networks (UAVSNs) can efficiently perform surveillance, connectivity, computing, and energy transfer services for ground users (GUs). These missions require trajectory planning, UAV-GUs association, task...
This paper proposes an extended comparative evaluation model framework (ECEMF) that highlights two objectives: (1) a specific economic evaluation method for the cost-optimisation of prefabricated lightweight system envelopes to achieve a greater valu...
This work couples high-fidelity moving-domain finite element compressible flow modeling with a Surrogate Management Framework (SMF) for optimization to effectively design a variable speed gas turbine stage. The superior accuracy of high-fidelity mode...
This paper presents an optimized hybrid deep learning model for power load forecasting—QR-FMD-CNN-BiGRU-Attention—that integrates similar day selection, load decomposition, and deep learning to address the nonlinearity and volatility of p...
We present OptimSolution, an open-source, cross-platform framework for the systematic benchmarking and analysis of continuous optimisation methods, available for Windows, Linux and macOS and operable via both a command-line interface (CLI) and a Qt-b...
Multi-target optimization management of reservoirs plays a crucial role in balancing multiple scheduling objectives, thereby contributing to watershed sustainability. In this study, a model was developed for the multi-target optimization scheduling o...
One of the most prevalent cancers is oral squamous cell carcinoma, and preventing mortality from this disease primarily depends on early detection. Clinicians will greatly benefit from automated diagnostic techniques that analyze a patient’s hi...
The use of machine-learning algorithms in optimizing the energy efficiency of HVAC systems has been widely studied in recent years. Previous research has focused mainly on data-driven model predictive controls and reinforcement learning. Both approac...
Dimensioning and assessment of a specific wind turbine imply iterative steps for design optimization, as well as load calculations and performance analyses of the system in various environmental conditions. However, due to the complexity of wind turb...
Electrocoagulation (EC) systems are regaining attention as a promising wastewater treatment technology due to their numerous advantages, including low system and operational costs and environmental friendliness. However, the widespread adoption and f...
Designing wind farms in complex terrain is an important task, especially for countries with a large portion of complex terrain territory. To tackle this task, an optimization framework is developed in this study, which combines the solution from a wi...
Optimizing warehouse operations is a strategic priority for ensuring the timely and efficient flow of materials in industrial environments. In contexts with limited digital infrastructure, organizations often face persistent challenges such as ineffi...
This work illustrates how a proposed method can be used to create optimization frameworks for early conceptual design studies and to increase overall knowledge at an early design stage. The method is intended to facilitate concept selection in challe...
The commercial space launch sector is currently undergoing a significant shift, with increasing competition and demand for launch services, as well as growing concerns about the environmental impact of rocket launches. To address these challenges, wi...
A framework is introduced for the systematic development of preparative chromatographic processes. It is intended for the optimal design of conventional and advanced concepts that exploit strategies, such as recycling, side streams, bypasses, using s...
Developing spacecraft for efficient aerocapture missions demands managing extreme aerothermal environments, precise controls, and atmospheric uncertainties. Successful designs must integrate vehicle airframe considerations with trajectory planning, a...
Building HVAC systems face significant challenges in energy optimization due to changing building characteristics and the need to balance multiple efficiency objectives. Current approaches are limited: physics-based models are expensive and inflexibl...
With the widespread adoption of wireless communication technologies in modern high-speed rail systems, the Train-to-Ground (T2G) communication system for Electric/Diesel Multiple Units (EMU/DMU) has become essential for train operation monitoring and...
This paper addresses the decentralized composite optimization problem, where a network of agents cooperatively minimize the sum of their local objective functions with non-differentiable terms. We propose a novel communication-efficient decentralized...
Fuzzy inference systems (FISs) are a key focus for decision-making in embedded systems due to their effectiveness in managing uncertainty and non-linearity. This study demonstrates that optimizing FIS hardware enhances performance, efficiency, and ca...
Solving of combinatorial optimization problems is a common practice in real-life engineering applications. Trusses, cranes, and composite laminated structures are some good examples that fall under this category of optimization problems. Those exampl...
Context: The increasing adoption of Internet of Things (IoT) technologies has transformed digital marketing into a software-intensive, data-driven ecosystem requiring continuous optimization under uncertainty. Existing decision-support approaches pri...
The optimal placement of robotic manipulators within industrial workstations is a critical problem that directly affects task feasibility, accessibility, and operational efficiency. Improper base positioning can lead to joint saturation, reduced mani...
The aerodynamic optimization of airfoil shapes remains a critical research area for enhancing aircraft performance under various flight conditions. In this study, the RAE 2822 airfoil was selected as a benchmark case to investigate and compare the ef...
In this paper, we investigate a simulation-based optimization framework that implements discrete-event simulation with evolutionary search methods to optimize stochastic manufacturing systems efficiently. The proposed methodology couples a Tecnomatix...
Nowadays, people like to travel to alleviate the stress and depression they experience in their busy lives, and if they can do so at a low cost, it will be even more beneficial to them. A traveler can choose to book a travel ticket themselves or to c...
Enhancing the sustainability of wastewater treatment plants (WWTPs) is crucial due to their manifold benefits, which encompass environmental preservation, cost reduction, and resource and energy conservation. The achievement of these advantages relie...
In this paper we present the design and implementation of a generic GA-based optimization framework iMASKO (iNL@MATLAB Genetic Algorithm-based Sensor NetworK Optimizer) to optimize the performance metrics of wireless sensor networks. Due to the globa...
This work presents a generalized framework for solving the inverse kinematics problem of robotic manipulators by introducing two approaches: optimization-based and learning-based approaches within a unified architecture. The optimization-based invers...
Amid the escalating climate crisis, integrating variable renewables into power systems demands innovative carbon-conscious grid management. This research presents a Graph Convolutional-Optimization Framework that synergizes Graph Convolutional Networ...
Spatiotemporal scale is a basic component of geographical problems because the size of spatiotemporal units may have a significant impact on the aggregation of spatial data and the corresponding analysis results. However, there is no clear standard f...
Currently, large language models (LLMs) have been utilized in many aspects of natural language processing. However, due to their significant size and high computational demands, large computational resources are required for deployment. In this resea...
In modern electronics, there are many inevitable uncertainties and variations of design parameters that have a profound effect on the performance of a device. These are, among others, induced by manufacturing tolerances, assembling inaccuracies, mate...
Effective Construction Site Layout Planning (CSLP) ensures the organized placement and sizing of temporary facilities, enhancing workflow and logistical efficiency. Poorly planned layouts, however, can increase material handling times, create bottlen...
As the complexity and functional integration of mechanism systems continue to increase in modern practical engineering, the challenges of changing environmental conditions and extreme working conditions are becoming increasingly severe. Traditional u...
Ship design is a particularly complex and time-consuming process, comprising a series of phases from concept to detail design. Ideally, the designer needs to deliver a design that complies with the operational and regulatory requirements, while at th...
The Trans-European Replacement Reserve Exchange (TERRE) project is the European implementation project for exchanging Balancing Energy (BE) from Replacement Reserves (RR). Its main objective is to operate a common European platform that gathers all R...
With the development of avionics systems towards high integration and high power density, the thermal management of electronic equipment in ATR chassis is facing severe challenges, and the extreme aviation environment further exacerbates the difficul...
The process parameter settings of electrolytic copper foil (ECF) electrodeposition face challenges due to insufficient data within individual production domains and barriers to cross-domain data sharing. Coordinating federated predictor training with...
In the real-world, symmetry or asymmetry widely exists in various problems. Some of them can be formulated as constrained multi-objective optimization problems (CMOPs). During the past few years, handling CMOPs by evolutionary algorithms has become m...
Despite advancing Internet of Things (IoT) technologies, road projects often rely on inaccurate supplier data, making it difficult to determine the cost, quantity, quality, and transportation duration of the needed materials. The wrong choice of mate...
Energy communities (EC) are expected to have a pivotal role to reach European decarbonization targets. One of the key aspects is the regulatory framework adopted by each Member State to properly manage such new customers’ aggregation. The paper first...
Biodegradable magnesium alloys have garnered increasing attention in recent years, with magnesium alloy–based biomedical devices being clinically used. Unlike biologically inert metallic materials, magnesium-based medical devices degrade during...
Current offshore wind farms (OWFs) design processes are based on a sequential approach which does not guarantee system optimality because it oversimplifies the problem by discarding important interdependencies between design aspects. This article pre...
Point cloud registration is a fundamental task in computer vision and graphics, which is widely used in 3D reconstruction, object tracking, and atlas reconstruction. Learning-based optimization and deep learning methods have been widely developed in...
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