In this research, the architecture and the functionalities of the LAMBDA (Laboratory of Aircraft Multidisciplinary Knowledge-Based Design and Analysis) framework for the design, analysis, and optimization of civil aircraft are presented. The framewor...
This paper presents an optimization-based framework for active vibration control of rotor bearing systems using external surface-bonded piezoelectric patches. The rotor bearing system is modelled using the Finite Element Method (FEM), enabling the co...
We propose a unified additive–multiplicative optimization framework, termed hybrid multiplicative gradient decomposition (HMGD), for training machine learning models. Unlike conventional gradient-based methods that rely solely on additive param...
Strategic cost optimization is a critical challenge for businesses aiming to maintain competitiveness in dynamic markets. This paper introduces Gen-Optimizer, a Generative AI-based framework designed to analyze and optimize business costs through int...
Dynamic multi-objective big data optimization problems (DMBDOPs) are challenging because of the difficulty of dealing with large-scale decision variables and continuous problem changes. In contrast to classical multi-objective optimization problems,...
In recent years, optimization algorithms have developed rapidly, especially those which introduce quantum ideas, which perform excellently. Inspired by quantum thought, this paper proposes a quantum dynamics framework (QDF) which converts optimizatio...
The combustion optimization problem of the circulation fluidized bed boiler is regarded as a difficult multi-objective optimization problem that requires simultaneously improving the boiler thermal efficiency and reducing the NOx emissions concentrat...
Portfolio optimization is a fundamental problem in financial theory, aiming to balance risk and return in asset allocation. Traditional models, such as Mean–Variance optimization, are effective, but often fail to account for diversification ade...
This paper presents a distributed computational framework for stochastic convex optimization problems using the so-called scenario approach. Such a problem arises, for example, in a large-scale network of interconnected linear systems with local and...
Optimal Power Flow Operation (OPFO) is a large-scale, nonlinear, and highly constrained optimization problem that plays a central role in achieving economical, reliable, and environmentally sustainable power system operation. Despite the widespread u...
Traditional mean–variance portfolio optimization proves inadequate for cryptocurrency markets, where extreme volatility, fat-tailed return distributions, and unstable correlation structures undermine the validity of variance as a comprehensive...
This study introduces a multi-criteria decision-making (MCDM) framework for optimizing multi-energy network scheduling (MENS). As energy systems become more complex, the need for adaptable solutions that balance consumer demand with environmental sus...
Recently, a population-based intelligent optimization algorithm research has been combined with multiple algorithms or algorithm components in order to improve the performance and robustness of an optimization algorithm. This paper introduces the ide...
The layout of emergency medical services (EMS) is of vital importance. A well-planned layout significantly impacts the timeliness of response and operational efficiency, which are crucial for saving lives and mitigating injury severity. This paper pr...
The three-dimensional (3D) reconstruction of buildings using photogrammetric point clouds is important for many applications, ranging from digital city construction to urban energy consumption analysis. However, problems such as building complexity a...
Water resources are a major concern for any socio-economic development. As the quality of many surface fresh water sources increasingly deteriorate, more pressure is being imparted into groundwater aquifers. Since groundwater and the aquifers that ho...
This study introduces a decision support framework that integrates aircraft trajectory optimization and arrival scheduling to facilitate efficient management of descent operations for arriving aircraft within terminal maneuvering areas. The framework...
Configuring a battery energy storage system (BESS) is an effective approach to alleviating the peak shaving and valley filling burden on conventional thermal power units. However, excessive capacity increases investment cost, whereas insufficient cap...
As the power grid expands, concerns about system computation speed and information privacy are becoming more critical. While distributed optimization methods protect individual privacy effectively, they struggle with computational efficiency in compl...
Traffic simulation, a tool for recreating real-life traffic scenarios, acts as an important platform in transportation research. Considering the growing complexity of urban mobility, various large-scale regional simulators are designed and used for r...
Personalized itinerary planning for large-scale passengers under resource constraints is a critical challenge in enhancing the operational efficiency and service quality of cruise tourism. Traditional clustering methods, which primarily rely on geome...
This study introduces a comprehensive modeling framework for the evaluation of automotive hydraulic shock absorbers, developed on the basis of an interdisciplinary coupled model that integrates the shock absorber and the servo-hydraulic test-rig subs...
Ensuring the safety of autonomous vehicles (AVs) in complex and high-risk traffic scenarios remains a critical unresolved challenge. Current AV planning methods exhibit limitations in generating robust driving trajectories that effectively avoid coll...
Property city is a newly emerging property service mode attracting widespread attention. Addressing the gap in quantitative analysis of the vehicle routing problem (VRP) of a property city based on quantitative analysis in existing studies, this stud...
This study used a Systemic Modeling technique, based on the methodologies of Churchman and Ackoff, to integrate and assess the subsystems regulating the functionality of a Rocket Candy (R-Candy) motor. The nozzle and combustion chamber design was imp...
This paper presents a resilience-driven probabilistic multiobjective framework for reactive power planning in islanded microgrids under extreme contingencies, explicitly integrating sustainability objectives and alignment with the United Nations Sust...
The good indoor light environment and comfort of the teaching space are very important for students’ physical and mental health. Meanwhile, China advocates energy conservation and emission reduction policies. However, in order to obtain lower b...
Decarbonizing production activities is a critical task in the transition towards carbon neutrality. Traditional carbon footprint accounting tools, such as life-cycle assessment (LCA) and the Greenhouse Gas Protocol, primarily quantify direct and indi...
To address the complex trade-offs among charging efficiency, battery lifespan, energy efficiency, and safety in high-power electric vehicle (EV) fast charging, this paper presents an intelligent control framework based on contrastive learning and man...
Background/Objectives: Brain tumors are among the most severe neurological disorders, and their variability in size, morphology, and anatomical location complicates early and accurate diagnosis. Although magnetic resonance imaging (MRI) is the most r...
Conventional shared energy storage (SES) allocation and coordinated operation mechanism are mismatched with the actual time-varying demand of the distribution system, resulting in low utilization of energy storage and renewable energy sources (RES),...
This paper presents a G-Agent, a large language model (LLM)-driven multi-agent framework that automates the optimization workflow for an axisymmetric cavity-based scramjet combustor. The framework integrates a supersonic compressible reacting flow so...
To reduce the fluctuation of renewable energy (RE) supply and improve the economic efficiency of the power grid, the energy local area network (ELAN), which is a subnetwork of the energy internet (EI), plays an important role in specific regions. Ele...
Underwater images often suffer from luminance attenuation, structural degradation, and color distortion due to light absorption and scattering in water. The variations in illumination and color distribution across different water bodies further incre...
Advanced deep reinforcement learning shows promise as an approach to addressing continuous control tasks, especially in mixed-autonomy traffic. In this study, we present a deep reinforcement-learning-based model that considers the effectiveness of le...
Artificial intelligence (AI) technology and the Industrial Revolution (4IR) have the potential to rapidly advance smart buildings, materials, and construction processes to meet global decarbonization goals. Current retrofit techniques can vary a grea...
Wing–diesel hybrid ships are a practical approach to sustainable maritime transport that harnesses wind energy to supplement diesel propulsion and reduce carbon emissions. The core optimization problem addressed in this study is the global ener...
Optimizing the design of Ceramic Composite Armor Systems (CCASs) is crucial for liberating redundant design space and enhancing ballistic performance. However, existing solution frameworks still exhibit deficiencies in handling multi-constrained opti...
A coupled multi-stage learning framework is presented for joint bit error rate (BER) prediction and beam angle optimization in massive multiple-input multiple-output (MIMO) systems under a controlled simulation protocol. Unlike purely sequential benc...
Achieving thermal comfort in social housing under variable and changing climates presents a critical challenge for sustainable building design and energy efficiency. This study develops a simulation-based multi-objective optimization framework to sup...
Thermally driven adsorption refrigeration offers a compressor-free pathway to sub-zero ice production from low-grade heat. Systematic design guidance for the 65–160 °C range remains limited: existing comparative studies lack consistent syst...
Shape optimization is a very time-consuming and expensive task, especially if experimental tests need to be performed. To overcome the challenges of geometry optimization, the industry is increasingly relying on numerical simulations. These kinds of...
In response to the safety threats posed by unauthorized unmanned aerial vehicles (UAVs), the importance of anti-UAV systems is becoming increasingly apparent. In tasks involving UAV detection, small UAVs are particularly difficult to detect due to th...
This paper investigates a distributed convex optimization problem whose objective contains three terms: a local smooth convex function, a local nonsmooth function, and a globally shared, possibly nonsmooth, nonseparable coupling function. To solve th...
28 August 2019
The objective of this study is to summarize the current general evaluation process that stakeholders use to evaluate single or multiple medical devices to select the optimal medical device. This study constructed a novel evaluation framework to selec...
The coordination of heterogeneous Unmanned Aerial Vehicles (UAVs) for complex, multi-stage tasks presents a significant challenge in robotics and autonomous systems. Traditional linear models often fail to capture the emergent synergistic effects and...
The study of evolutionary algorithms (EAs) has witnessed an impressive increase during the last decades. The need to explore this area is determined by the growing request for design and the optimization of more and more engineering problems in socie...
This paper presents a taxonomy-based survey of AI-driven network optimization mechanisms relevant to the transition from fifth generation (5G) to sixth generation (6G) mobile communication systems. In contrast to earlier generational shifts that are...
Uncoordinated driving behavior is one of the main reasons for bottlenecks on freeways. This paper presents a novel cyber-physical framework for optimal coordination of connected and automated vehicles (CAVs) on multi-lane freeways. We consider that a...
This paper presents a study on the development of a hybrid modeling framework for the optimal operation of microgrids based on renewable energy resources. Accurate prediction of both renewable energy generation and consumer demand is crucial for the...
of 664