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217 articles for “constrained optimization”
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An Optimal Bidding Strategy for Social Welfare Maximization of Microgrid
Abstract: Competition in power markets implies benefit to the generators as well as customer. The uncertain nature of bids and behavior of renewables makes the bidding strategy more complex. The power market comprises of Generation companies (GENCOS), Transmission companies (TRANSCOs) and Distribution companies (DISCOs) which actively participate in the auction process. In this paper, a new bidding strategy for a microgrid in day-ahead market is proposed for social welfare maximization considering …
Published in Journal Of Network security · Vol. 8, Issue 1, 2020 · pp. 11–21 Read article
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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 · pp. 19–28 Read article
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JATAYU: A Stereo Vision–Based UAV for Autonomous Navigation and Human Following in GPS-Denied Environments
Abstract: Traditional unmanned aerial vehicle (UAV) systems primarily rely on Global Positioning System (GPS)-based navigation and conventional computer vision techniques. However, these approaches face significant challenges in GPS-denied environments, such as dense urban areas, indoor spaces, and disaster-affected regions where GPS signals may be weak, unavailable, or unreliable. In addition, limitations in real-time processing, object detection accuracy, and environmental perception can reduce UAV effectiveness in dynamic and unpredictable situations. This paper …
Published in International Journal on Drones · Vol. 2, Issue 2, 2026 · pp. 30–38 Read article
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Comparative Analysis of Energy Storage System’s Hybridization for Electric Vehicles: Evaluating Lithium-Ion Batteries, Supercapacitors, and Fuel Cells on Performance Metrics
Abstract: High-performance energy storage systems (ESS) in electrically powered cars are becoming more and more necessary as transportation options become more environmentally conscious. This research provides a thorough comparison of hybrid energy storage systems (HESS) that link fuel cell technology, supercapacitors, and batteries made of lithium ion. Critical performance metrics are assessed for each technology, including energy density, power density, efficiency, lifecycle durability, thermal performance, cost and sustainability. It summarizes the …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 3, Issue 1, 2025 · pp. 12–29 Read article
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Design Optimization of A Riveted Joint Used in Back Plate of A Pendulum Absorber Assembly
Abstract: Riveted joints are widely used for fastening sheet metal components. Cylindrical rivets are generally preferred but due to space constraints in some cases, other geometries are being explored. In this work, a practical case of a rectangular riveted assembly for back plate of pendulum absorber assembly commonly used in modern vehicles for damping secondary vibrations is considered and an iterative simulation study for design optimization has been conducted using finite …
Published in Trends in Mechanical Engineering & Technology · Vol. 5, Issue 1, 2015 · pp. 36–50 Read article
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Comparison of Hard Wood Functional Parameters on the Deliverability using Buckingham Pi Theorem: The Concept of Procurement
Abstract: This investigation was able to address the effect of wood density and weight on the tensile strength and deliverability of the truck performance and as medium to forecast the procurement plan for cost optimization. This was achieved using the Buckingham Pi Theorem by considering the necessary constrain factors as presented in the development of the model. Indeed, the study demonstrates the significance of wood density and wood weight on truck …
Published in Journal of Petroleum Engineering & Technology · Vol. 12, Issue 3, 2022 · pp. 19–27 Read article
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Architectural Evolution of RISC Processors: From Early Research Prototypes to Modern Industrial Implementations
Abstract: This paper surveys the architectural evolution of Reduced Instruction Set Computer (RISC) architectures from early research prototypes to modern industrial processors, tracing four decades of design refinement across academic, embedded, server, mobile, and open- hardware ecosystems. Core ISA principles, pipeline evolution, compiler–hardware co-design, and quantitative performance modeling are analyzed through four representative industrial implementations: MIPS 74K, SPARC T4, ARM Cortex-A72, and SiFive U74 (RISC-V). Each processor is examined in terms …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 · pp. 29–39 Read article
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Machine Learning-Based Task Scheduling and Resource Optimization in Edge-IoT Systems
Abstract: The rapid expansion of Internet of Things (IoT) applications has introduced significant challenges in managing computational workloads across distributed edge environments. Edge- IoT systems are characterized by limited computational capacity, dynamic task arrivals, and strict latency constraints. Traditional heuristic-based scheduling techniques often fail to adapt to fluctuating workloads and heterogeneous resource availability. This study proposes a machine learning-based task scheduling and resource optimization framework for Edge-IoT systems. The proposed model …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Group-Theoretic Symmetry Indices for Modular Building Layouts under Seismic Load Redistribution
Abstract: Symmetry in modular buildings operates simultaneously as an architectural language, a structural regularizer, and a computational design variable. This paper develops a group-theoretic framework for evaluating and optimizing plan symmetry in modular buildings subjected to seismic load redistribution. The building layout is modeled as a finite occupancy–stiffness field defined on a rectangular lattice, where each module encodes both mass and stiffness contributions. Planar reflections and quarter-turn rotations are represented as …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 01–07 Read article
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Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 · pp. 10–22 Read article
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Development and Optimization of Orally Disintegrating Tablets (ODTs) Containing Standardized Curcumin Extract for Enhanced Bioavailability and Patient Compliance
Abstract: This research centers on creating and perfecting orally disintegrating tablets with standardized curcumin extract to both increase its bioavailability and promote better patient adherence. Although curcumin has numerous therapeutic applications. It remains clinically ineffective due to its poor aqueous solubility and bioavailability constraints. The development of orally disintegrating tablets involved direct compression with various levels of superdisintegrants including sodium starch glycolate and cross povidone to address existing challenges. Research teams …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 3, 2025 · pp. 1–06 Read article
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Model Predictive Control for a Distillation Column Model
Abstract: Model Predictive Control (MPC) is a multivariable control (requires specific handling of each input as coupling and interaction is of a far greater effect) and uses the internal dynamic model of the process, past control moves and an optimization cost function over the receding prediction horizon, to calculate the optimum control moves. In this paper, the relation between MPC parameters was studied on process constraints. Conical tank level single-input-single-output (SISO) …
Published in Journal of Mechatronics and Automation · Vol. 1, Issue 3, 2014 · pp. 11–19 Read article
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AI-Driven Topology Optimization of Woven Fiber-Reinforced Composite Chassis Structures for Electric Vehicles Under Crash Loading
Abstract: The structural design of an electric vehicle (EV) chassis represents a unique engineering challenge to achieve minimal weight while meeting occupants' safety requirements during high-energy crash conditions without compromise to the battery housing's integrity or the geometrical constraints of the electric powertrain package. In this paper, a single framework is proposed to integrate physics-based artificial intelligence (AI) surrogate models using PINNs, CNN-accelerated topology optimization, and FEA to design woven fiber-reinforced …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 72–89 Read article
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Artificial Intelligence and Edge Computing in Oil and Gas: Applications, Architectures, and Operational Realities
Abstract: Artificial intelligence has arrived in oil and gas, and unlike some previous waves of digital enthusiasm in the sector, this one is sticking. Saudi Aramco analyses approximately 10 billion data point every day and reported USD 4 billion in technology-driven operational gains in 2024. ExxonMobil uses AI to increase shale well output by more than 5 percent. Shell has deployed machine learning across more than 10,000 assets using C3.ai to …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 01–06 Read article
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Photovoltaics and Thermal Solar Technologies: Innovations for Sustainable Heating, Cooling, and Energy Efficiency
Abstract: Developments in renewable energy technology, in particular photovoltaics (PV) and solar thermal systems, have been fueled by a rising demand for energy worldwide and the pressing need to slow down climate change. These technologies provide greener options for heating, cooling, and energy production by lowering dependency on fossil fuels and greenhouse gas emissions. This study examines developments in solar thermal and photovoltaic technologies, their uses in commercial, industrial, and residential …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 30–37 Read article
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INTELLIGENT MANAGEMENT OF CONSTRUCTION PROJECTS: THE NEXUS OF HUMAN AND ARTIFICAIL EXPERTISE
Abstract: Conversations about digitalization and artificial intelligence (AI) have continued to gain traction in the project management discourse. Although human expertise remains the hallmark of professionalism in the construction industry, AI has emerged as the newest wave of digital technological innovation, which can significantly elevate human productivity in the performance of project management functions. However, for project management professionals in the Nigerian construction industry, the potential of AI is both thrilling …
Published in Journal of Production Research & Management · Vol. 15, Issue 3, 2025 · pp. 16–24 Read article
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Develop the Design of Sustainable Polymer Materials: Applying Reinforcement Learning, IoT-Enabled Monitoring, and Data-Driven Manufacturing Approaches
Abstract: Sustainable polymer materials development is a must due to resource constraints, environmental concerns, and the demand for designed materials with high performance. When it comes to material optimization, energy utilization, process unpredictability, and lifecycle sustainability, traditional polymer production methods have their challenges. Reinforcement Learning (RL), Internet of Things (IoT) monitoring, and data-driven production are utilized in the design and manufacturing of sustainable polymer materials. It is recommended to use Internet …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1207–1231 Read article
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A Review on Design Optimization of Automotive Conventional Differential System for Rear Wheel Drive
Abstract: The following review paper provides a thorough explanation of the limitations of the automotive conventional differential system under various circumstances and suggests a viable solution for each constraint by enhancing the differential unit's design and construction. The conventional differential used in automotive (CAR, TRUCKS etc.) is the system which is used to transmit power from the engine to the rear wheels of the vehicle via the propeller shaft, hence we …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 1, Issue 2, 2023 · pp. 39–51 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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Fertile Data: Advanced Strategies for Crop Optimization Through Machine Learning Processing
Abstract: The venture, titled "FertileData: Advanced Strategies for Crop Optimization Through Machine Learning processing" is created utilizing HTML, CSS, and JavaScript for the front conclusion, and Python for the back conclusion. In a nation like India, where a noteworthy parcel of the populace depends on agribusiness for their vocation, joining progressed advances such as Machine Learning and Profound Learning into cultivating hones can revolutionize the industry. This venture presents a user-friendly …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 2, 2025 · pp. 25–35 Read article