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88 articles for “Achieving multi-objectives”
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Achieving Multi-objectives Using a Single Neural Network
Abstract: Achieving multi-objectives using a single neural network is a research area that aims to develop techniques to optimize multiple objectives simultaneously using a single neural network. This approach can be applied in various fields, such as image and speech recognition, robotics, and natural language processing, to achieve better performance and reduce the complexity of the models. The key challenge in this area is to balance the trade-off between different objectives …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 9, Issue 3, 2022 · pp. 1–15 Read article
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Optimization of Resin 3D Printing Process Parameters for Enhanced Dimensional Accuracy and Surface Roughness Using Hybrid Algorithm
Abstract: The advent of 3D printable dental resin has paved the way for minimally invasive dentistry, which helps to retain healthy tooth structure while yet producing pleasing aesthetic outcomes. However, printing these dental resins is being researched to improve their durability and therapeutic efficacy. Frontiers in dental restoration research can aim to fabricate occlusal appliances using resins with optimized parameters for enhanced functionalities. The present study aims to analyze the dimensional …
Published in Journal of Polymer & Composites · Vol. 11, Issue 3, 2023 · pp. 26–37 Read article
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Generative Design of Bioactive Orthopedic Composites for Fracture Repair Using an Integrated Conditional GAN–Transformer Framework: A Multi-Objective Approach
Abstract: Orthopedic composite implants for fracture repair must simultaneously satisfy conflicting mechanical and biological demands: high fracture toughness, sufficient compressive stiffness, and bioactive surface chemistry enabling osteoblast adhesion and mineralization. Existing design approaches rely on trial-and-error experimentation, yielding sub-optimal trade-offs between these objectives. This paper presents an integrated conditional Generative Adversarial Network–Transformer (cGAN-T) framework for fully computational, multi-objective generative design of hydroxyapatite (HA)-reinforced polymer composite microstructures targeting Orthopedic fracture repair. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 21–35 Read article
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TOPSIS-Driven Optimization of FFF Process Parameters for Mechanical Strength Enhancement
Abstract: In this study, the application of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for optimizing Fused Filament Fabrication (FFF) process parameters to enhance the tensile and flexural strength of Polylactic Acid (PLA) material-based 3D printed components is explored. This investigation delves into the intricate relationship between key parameters, such as layer height, print speed, infill density, print temperature, and nozzle diameter, and their impact …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 246–255 Read article
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Generative AI-Driven Design Optimization of Lightweight Polymer Composites for Electric Vehicles
Abstract: Lightweight polymer composites are increasingly important for electric vehicles, where mass reduction must be achieved without compromising structural performance, thermal stability, manufacturability, or material reliability. This study develops a generative AI-driven inverse-design framework for identifying experimentally credible lightweight polymer-composite configurations under coupled EV-oriented constraints. Public experimental polymer-composite datasets were integrated through leakage-controlled preprocessing and group-aware validation. A multi-task neural surrogate predicted mechanical response, while a conditional variational autoencoder explored feasible …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Optimization of Process Parameters in Wire EDM of HCHCrD2 using RSM-based Multi-objective Genetic Algorithm
Abstract: While precision is of paramount importance in machining of high strength conductive materials, Wire Electrical Discharge Machining (WEDM) is preferred. In the present work, experimental study has been carried to identify the appropriate process parameter settings for wire electrical discharge machining of high carbon high chromium D2 steel (HCHCrD2). The process parameters such as pulse peak current, pulse duration, pulse-off time, wire feed, wire tension and flushing pressure are considered. …
Published in Journal of Mechatronics and Automation · Vol. 5, Issue 1, 2018 · pp. 6–10 Read article
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Optimization of Sustainable Electrochemical Machining Parameters for Polymer based Materials Using AHP Integrated TOPSIS Method
Abstract: The current paper describes the use of the AHP-TOPSIS method to optimize process parameters in sustainable electrochemical machining of polymer composites. Combine lightweight polymer matrices with reinforcing particles or fibers such as TiB₂, SiC, or Al₂O₃, offering high strength-to-weight ratio, corrosion resistance, and design flexibility, making them ideal for aerospace and automotive applications. Non-conductive and heterogeneous nature poses challenges during electrochemical machining, as it affects current distribution and material removal …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1048–1059 Read article
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AI-Enabled Optimization of Additively Manufactured Composite Materials for Enhanced Mechanical and Thermal Performance
Abstract: This paper discusses the optimization of multi-objective optimization of enhanced coupling of heat and mechanical properties of 3D printed polymer composite materials by artificial intelligence (AI), as a component of a multi-objective optimization framework. It aims at development of nonlinear printing parameters and material properties relationships to achieve maximum tensile strength and thermal conductivity in polymer composites produced through fused deposition modeling (FDM). Short carbon fiber reinforcement was used to …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 867–891 Read article
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Optimization of Combined Cooling, Heating and Power Plant
Abstract: In today’s world where there are energy crises, there is a need to conserve the same. In order to conserve the energy, it is imperative to utilize its available forms as per the requirement that arise from the end user. In this paper, modeling and optimization of a combined cooling, heating and power (CCHP) plant is done wherein minimization of exergy destruction is set as an objective function. Electric and …
Published in Emerging Trends in Chemical Engineering · Vol. 4, Issue 1, 2017 · pp. 7–14 Read article
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An Experimental Study on Multi-Criteria Parameters Optimization of Process for Al6351/SiC/Gr Metal Matrix Composites Using AHP-TOPSIS Approach
Abstract: This research focuses on optimizing the process parameters of Wire Electrical Discharge Machining (WEDM) for a hybrid Metal Matrix Composite (MMC) comprising Al6351 aluminum alloy reinforced with 4% SiC and 6% graphite (Gr), fabricated via squeeze casting. This technique enables the formation of dense, defect-free composites with uniform reinforcement distribution, enhancing both mechanical properties and structural integrity. Microstructural characterization using Scanning Electron Microscopy (SEM) confirmed the even dispersion and bonding …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 303–319 Read article
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Reward-Aligned Reinforcement Learning from Human Feedback for Emotion-Sensitive Large Language Model Therapists: Balancing Empathetic Engagement, Boundary Safety, and Clinical Accountability
Abstract: The deployment of large language models (LLMs) in mental health therapy contexts introduces a critical alignment challenge: these systems must simultaneously cultivate genuine empathic rapport, observe clinically grounded safety boundaries, and remain auditable under institutional accountability frameworks. Existing reinforcement learning from human feedback (RLHF) pipelines optimize for a scalar reward signal that is demonstrably insufficient for the multi-objective, temporally extended nature of therapeutic conversation. This paper presents RA-RLHF-T (Reward-Aligned RLHF …
Published in International Journal of Tropical Medicines · Vol. 3, Issue 2, 2026 Read article
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Artificial Intelligence-Assisted Multi-Objective Optimization of Agricultural Biomass-Reinforced Polymer Composites
Abstract: Agricultural biomass can reduce the environmental burden of polymer composites, yet its heterogeneous structure creates competing effects on strength, moisture resistance, density, and process ability. This study developed an artificial intelligence-assisted framework for balanced composite formulation. Experimental data of agricultural biomass reinforced polymer composites were gathered, harmonized and validated using leakage-controlled validation. The mechanical and physical properties were predicted by artificial neural networks and conventional regression models. Explainable analysis gave …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 202–222 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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Multi-Objective Optimization of Polymer-Based Functionally Graded Composites for Lightweight Structures
Abstract: Functionally graded composites (FGCs) improve lightweight structural performance by allowing material properties to change smoothly across a component. Polymer-based FGCs (P-FGCs), in particular, are gaining prominence in aerospace, automotive, and biomedical industries due to their excellent strength-to-weight ratio, tunability, and ease of processing. However, optimizing these materials for lightweight structural applications requires addressing conflicting design objectives, such as maximizing stiffness while minimizing weight or enhancing thermal resistance while maintaining manufacturability. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 961–973 Read article
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Toxicological Profiling and Safety Assessment of NASAT 2.0: A Conceptual Framework for Adaptive Nanoparticle Therapy in Rabies
Abstract: Rabies, caused by the highly neurotropic Rabies lyssavirus, remains one of the most enigmatic and universally lethal infectious diseases known to modern medicine. Once clinical symptoms manifest following successful neuroinvasion, the fatality rate approaches absolute certainty (approximately 99.9%), a staggering statistic that has remained largely unchallenged despite massive, concurrent advances in modern virology, critical care medicine, and cellular immunology. Current late-stage therapeutic protocols, most notably the widely debated Milwaukee Protocol, …
Published in Research and Reviews: A Journal of Toxicology · Vol. 16, Issue 2, 2026 · pp. 1–19 Read article
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Machining-Induced Surface Integrity Optimization of High-Carbon Alloy Steel for Enhanced Polymer–Metal Composite Interface Performance
Abstract: The functional performance and structural reliability of polymer–metal hybrid composites are strongly influenced by the surface integrity of metallic substrates used for interfacial bonding and load transfer. In this context, machining-induced surface characteristics play a critical role in determining adhesion behavior, dimensional stability, and mechanical compatibility within composite architectures. The present study investigates the hard turning performance of a newly developed high-carbon alloy steel intended for composite-integrated structural applications, with …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1531–1546 Read article
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Multi Objective Optimization of Lifting Hook Strength for Hitachi Sumitomo Systems Using Cross Sectional Variations
Abstract: Material handling equipment refers to a broad category of mechanical systems used for the movement, storage, regulation, and safeguarding of materials and products throughout different stages such as manufacturing, distribution, usage, and disposal. These systems form an integral part of industrial operations by facilitating efficient handling processes. Typically, material handling equipment can be grouped into four primary classifications: storage and handling devices, engineered systems, industrial transport vehicles, and bulk material …
Published in Trends in Machine design · Vol. 13, Issue 2, 2026 · pp. 1–15 Read article
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AI-Driven Multi-Objective Optimization of Conductive Polymer Composites for High-Performance Flexible Electronics
Abstract: The development of conductive polymer composites (CPCs) is critical for advancing flexible and wearable electronic technologies. However, the conventional trial-and-error approach to material formulation is time-consuming and often inefficient due to the high-dimensional nature of the design space. This study introduces a novel AI-driven framework that integrates machine learning (ML) with multi-objective optimization to accelerate the discovery of high-performance CPCs. A dataset of 1,000 experimentally reported formulations was compiled, capturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 734–745 Read article
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Integrating Genetic Algorithms with Lean Manufacturing for Enhanced Production Efficiency
Abstract: Lean manufacturing is a well-established philosophy focusing on the systematic reduction of waste and the ongoing development of value supplied to the customer. It emphasizes efficiency, quality, and adaptability through ideas such as just-in-time production, continuous improvement (Kaizen), and value stream optimization. However, the increased complexity of modern production systems, driven by global rivalry, product variety, and rapid technology innovation, has shown the limitations of classic lean tools in achieving …
Published in Journal of Production Research & Management · Vol. 15, Issue 3, 2025 · pp. 38–43 Read article
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Traffic Aware Coloring based Scheduling Scheme for Mobile Wireless Body Area Networks
Abstract: AbstractEvolution in the wireless technology and supportive infrastructure offer innovative opportunities for healthcare and fitness monitoring applications without restricting activities of the user. The wireless body area networks (WBAN) have ability to bring revolution in the healthcare field. In spite of this ability WBAN have some technical challenges that need to be researched. The biggest challenge in WBAN is to provide quality of service. Many scheduling techniques have been proposed …
Published in Journal of Electronic Design Technology · Vol. 8, Issue 3, 2017 · pp. 8–11 Read article