Sustainable water management requires integrated approaches balancing competing demands and environmental sustainability. This study introduces the Sustainable Water Optimization Tool (SUWO), an open-source, Python-based simulation-optimization frame...
The quality of machine learning models can suffer when inappropriate data is used, which is especially prevalent in high-dimensional and imbalanced data sets. Data preparation and preprocessing can mitigate some problems and can thus result in better...
Water distribution networks (WDNs) have a crucial task: to reliably provide sufficient and high-quality water while optimizing financial resources. Achieving both reliability and resilience is vital. However, oversizing capacities can be costly and d...
This paper proposes an integrated sustainable optimization framework consisting of three modules to optimize vehicle routes, traffic signals, and CAV trajectories at the network level. The route guidance module determines optimal routes to maximize n...
This article presents a resilient Integrated Resource Planning (IRP) framework designed for transmission systems, with a specific focus on analyzing and optimizing responses to High-Impact Low-Probability (HILP) events. The framework aims to improve...
Background: Emerging pandemics can rapidly overwhelm hospital capacity, leading to increased mortality and healthcare costs. Objective: We develop an optimization-based framework that dynamically schedules hospital beds across multiple facilities to...
The main motivation for this study is to develop a predictive framework that provides high accuracy at lower computational and experimental costs, resulting in better decision-making in the chosen application domain. Artificial neural networks (ANNs)...
Waverider is a hypersonic vehicle that improves the lift-to-drag ratio using the shockwave attached to the leading edge of the lifting surface. Owing to its superior aerodynamic performance, it exhibits a viable external configuration in hypersonic f...
Placement is crucial in physical design flow with significant impact on later routability and ultimate manufacturability in terms of performance, power, and area (PPA), which may deviate from finding the optimal solution and/or lead to unnecessary it...
This study presents a mathematical optimization framework for spoken language recognition (SLR) based on the integration of deep learning, metaheuristic optimization, and neuro-fuzzy classification components into a single recognition pipeline. The p...
Essentially, the solution to an attribute reduction problem can be viewed as a reduct searching process. Currently, among various searching strategies, meta-heuristic searching has received extensive attention. As a new emerging meta-heuristic approa...
This paper proposes a design-technology co-optimization (DTCO) framework applicable to advanced technology nodes, which accelerates the process optimization exploration for such nodes. Developing automatic parameter extraction algorithms tailored for...
Carbon Capture and Storage (CCS) stands as a pivotal technological stride toward a sustainable future, with the practice of injecting supercritical CO2 into subsurface formations being already an established practice for enhanced oil recovery operati...
Park-and-ride (P&R) facility location optimization involves coupled facility-opening decisions and probabilistic traveler allocation. This study develops a Branch-and-Benders-Cut Decomposition (B&CBD) framework for exact optimization under a...
The deep learning paradigm is progressively shifting from non-smooth activation functions, exemplified by ReLU, to smoother alternatives such as GELU and SiLU. This transition is motivated by the fact that non-differentiability introduces challenges...
Model-based design principles have received considerable attention in biotechnology and the chemical industry over the last two decades. However, parameter uncertainties of first-principle models are critical in model-based design and have led to the...
The groove curvature coefficient plays a critical role in determining the thermo-mechanical performance of angular-contact ball bearings. However, its optimization remains challenging due to strong nonlinear coupling among stress, stiffness, heat gen...
Blockchain technology has transformed modern digital ecosystems by enabling secure, transparent, and automated transactions through smart contracts. However, the increasing complexity of these contracts introduces significant challenges, including hi...
Quality management in construction projects is critical for ensuring client satisfaction, minimizing rework, and achieving cost efficiency in an industry characterized by a long history of cost overruns. Traditional quality assurance and control (QA/...
Artificial intelligence algorithms need an external computing device such as a graphics processing unit (GPU) due to computational complexity. For running artificial intelligence algorithms in an embedded device, many studies proposed light-weighted...
The adaptive façades serve as the interface between the indoor and outdoor energy of the building. Adaptive façade optimization design can improve daylighting performance, the thermal environment, view performance, and solar energy util...
As a new mode of transportation, the underground logistics system (ULS) has become one of the solutions to the problems of environmental pollution and traffic congestion. Considering the environmental and economic factors in urban logistics, this pap...
This paper presents a decentralized informatics, optimization, and control framework to enable demand response (DR) in small or rural decentralized community power systems, including geographical islands. The framework consists of a simplified lumped...
Decentralized sustainable microgrids are emerging as a promising approach for addressing the increasing complexity of modern power systems while ensuring reliable and efficient operation. A fundamental driver of this transition is the partitioning of...
This paper proposes an optimization-based framework to determine the type of nonlinear model present and identify its parameters. The objective in this optimization problem is to identify the parameters of a nonlinear model by minimizing the differen...
The Anatolian Caracal Optimization Algorithm (ACOA), a swarm-based optimization approach inspired by nature, approximately describes the characteristic hunting strategy of the Anatolian caracal, shaped by its superior auditory–visual perception...
With rapid urbanization, the utilization of underground space has become an important part of infrastructure. However, the stability of underground spaces such as large caverns remains a key challenge in civil engineering throughout the lifecycle of...
Soil and groundwater systems have natural attenuation potential to degrade or detoxify contaminants due to biogeochemical processes. However, such potential is rarely incorporated into active remediation strategies, leading to over-remediation at man...
This paper presents a hybrid framework for multi-stock trading that combines the decision-making ability of Deep Q-Networks (DQN) with the allocation precision of portfolio optimization models. Realistic markets are noisy and non-stationary, and comp...
In this work, a novel optimization framework, based on a Multi-Disciplinary Optimization (MDO) procedure, applied to the vibro-acoustic Finite Element Method (FEM) model of an aircraft fuselage mock-up, is proposed. The MDO procedure, based on an Eff...
Maximizing the dominant Lyapunov exponent
Conventional thresholding methods for rotorcraft Health and Usage Monitoring Systems (HUMS) often neglect flight-condition variability, resulting in frequent false alarms. To address this, a flight-state-driven threshold optimization framework that e...
Addressing building vulnerability to climate hazards requires advanced tools to support adaptation decisions. To this end, the current study presents an Agentic Artificial Intelligence (Agentic AI) Optimization framework to enhance the climate resili...
The liver performs numerous essential metabolic and regulatory functions; however, chronic alcohol consumption remains a major cause of hepatic disease. Consequently, the early and accurate prediction of alcohol-related liver disorders is of consider...
In this paper, a multi-objective optimization framework for electric motors and its validation is presented. This framework is suitable for the optimization of design variables of electric motors based on a predetermined driving strategy using MATLAB...
In a time where sustainability and CO2 efficiency are of ever-increasing importance, heating systems deserve special considerations. Despite well-functioning hardware, inefficiencies may arise when controller parameters are not well chosen. While mon...
Improving indoor acoustic comfort in buildings remains challenging for conventional acoustic design methods because they often rely on empirical formulas, static databases, and limited adaptability to dynamic environmental changes. To address these l...
Design and manufacturing processes are entering into a new era as novel methods and techniques are constantly introduced. Currently, 3D printing is already established in the production processes of several industries while more are continuously bein...
This paper establishes a comprehensive statistical framework for analyzing quantum teleportation protocols under realistic noisy conditions. We develop novel mathematical tools to characterize the complete statistical distribution of teleportation fi...
We investigate the general iterative controller tuning (ICT) problem, where the task is to find a set of controller parameters that optimize some user-defined performance metric when the same control task is to be carried out repeatedly. Following a...
Efficient supply–demand management in Product-as-a-Service (PaaS) markets requires tools to evaluate pricing strategies while integrating sustainability goals like reuse, efficiency, and carbon footprint reduction. This paper introduces a decla...
Network reconfiguration is an effective way to avoid severe, large-scale power outages and to improve the resilience of active distribution networks (ADNs). Furthermore, the rapid development of distributed energy resources (DERs) provides new perspe...
This paper proposes an optimal operational framework for enhancing the economic, technical, and environmental performance of a renewable energy-based microgrid. The proposed system integrates photovoltaic (PV) generation, wind turbines (WTs), battery...
The Bi-directional Evolutionary Structural Optimization (BESO) method, owing to its algorithmic simplicity and strong scalability, has emerged as one of the most prevalent topology optimization methodologies in current research and industrial applica...
Project MOEEBIUS focus is the reduction of the gap between predicted and actual energy performances in buildings. This project will introduce a Holistic Energy Performance Optimization Framework with new tools and methodologies that enhance current b...
Each year, inventory decisions made under demand uncertainty generate substantial economic losses, reflecting a persistent disconnect between forecasting models and the operational decisions they are intended to support. This paper addresses this gap...
Aquaculture development increasingly faces the dual requirement of increasing economic output and reducing environmental pressure under limited aquatic resources. Existing studies have examined aquaculture efficiency, environmental performance, and p...
Because of the increasing concern regarding environmental sustainability, manufacturing equipment faces a challenge to optimize carbon emissions from a life-cycle perspective. Current approaches lack the overall low-carbon optimization flow guidance...
Geothermal power plants are excellent resources for providing low carbon electricity generation with high reliability. However, many geothermal power plants could realize significant improvements in operational efficiency from the application of impr...
Multi-objective optimization has become an indispensable tool for solving engineering design and manufacturing problems involving multiple conflicting objectives. This paper presents a novel parameter-less multi-objective optimization (MOO) framework...
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