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96 articles for “cost optimization”
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Applying Kruskal's Algorithm in Supply Chain Management for Cost-Effective Network Optimization
Abstract: Transportation route optimization and cost reduction are major difficulties in today's dynamic and complicated supply chain systems. To produce economical and effective network designs, this study investigates the use of Kruskal's algorithm for supply chain network optimization. The algorithm guarantees that all supply chain nodes, including delivery hubs, warehouses, and distribution centers, relate to the lowest possible total transportation cost by building the minimum spanning tree (MST). The study shows …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 49–54 Read article
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A Mathematical Perspective on Recent Cloud-Computing Trends for Scalable and Secure Social-Media Platforms
Abstract: Cloud computing underpins modern social-media platforms by providing elastic compute, storage, and data-processing pipelines capable of absorbing highly bursty workloads. This paper surveys recent cloud-native trends—serverless and event-driven design, container orchestration, edge/CDN offload, streaming analytics, and privacy-enhancing security controls—and formalizes their impact through a compact mathematical model. We express workload volatility using arrival-rate functions, use queueing-based capacity sizing to derive auto-scaling rules, and formulate an optimization objective that balances cost …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 35–40 Read article
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Virtual Machine Cost & Computing comparison between cloud service
Abstract: Cloud computing has revolutionized enterprise IT infrastructure with virtual machines forming the cornerstone of Infrastructure as a Service deployment. This study provides a detailed comparative evaluation of virtual machine pricing and computational performance among three leading cloud computing platforms: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Through quantitative analysis of current pricing data from September 2025, independent performance benchmarks from Cockroach Labs 2021 Report, and market …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 2, 2026 Read article
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A Review on Digital Twin Technology in Robotics
Abstract: Digital Twin (DT) technology has emerged as a transformative concept in robotics and automation, enabling virtual representation of physical systems, real-time monitoring, and performance optimization. This review explores the foundations of Digital Twin, its integration in robotic systems, key enabling technologies, applications, current challenges, and future research directions. The paper concludes by highlighting how Digital Twin transforms design, control, prediction, and human-robot collaboration.Digital Twin technology is transforming the field of …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
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Optimizing Manufacturing Processes with Taguchi Method in Production Engineering
Abstract: The Taguchi Method, pioneered by Genichi Taguchi, stands as a powerful optimization tool within the realm of production engineering. This paper delves into the principles, applications, and significance of the Taguchi Method in enhancing manufacturing processes. With a focus on minimizing variation and improving performance, this methodology plays a crucial role in addressing challenges faced by industries in their pursuit of operational excellence. The core components of the Taguchi Method, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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A Lightweight Cost-Sensitive Explainable Ensemble Framework for Early Heart Disease Risk Prediction
Abstract: Cardiovascular disease is still one of the leading causes of death, and hence, the early prediction of risk is a very important task in preventive medicine. Although recent studies have shown encouraging results in the application of machine learning algorithms to the prediction of heart disease, it has been noticed that most of the algorithms are more concerned with accuracy-driven optimization than the concerns of safety and false negatives. In …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Comparative Performance Study: Deterministic vs. Probabilistic Models in Retail Chains
Abstract: The finished goods, raw materials, and product stock that a business has on hand for sale are referred to as inventory. They enable the companies to achieve their sales levels and are a chance to cost control and decision making. It is a huge asset to a manufacturing firm. Inventory model permits forecasting of quantities of raw material, inventory and spare parts of the equipment to a very high level …
Published in Recent Trends in Mathematics · Vol. 2, Issue 1, 2025 · pp. 1–6 Read article
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Prediction of Depth-Induced Stress Distribution and Maintenance Cost Implications for Submerged Structural Components
Abstract: This study investigates the influence of water depth on stress distribution and structural integrity of submerged mechanical components . Structural models fabricated from mild steel, stainless steel, carbon steel, and copper alloy were examined under hydrostatic loading corresponding to water depths between 30 cm and 150 cm. Results indicate that normal and shear stresses increased proportionally with depth due to intensified hydrostatic pressure. Mild steel exhibited the highest stress concentrations, …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 29–35 Read article
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A Sustainable EOQ Model for Declining Products Incorporating Cubic Demand, Variable Deterioration, Partial Backlogging, and Carbon Emission Optimization
Abstract: In this paper proposes a sustainable Economic Order Quantity (EOQ) model for inventory systems involving decaying items under cubic time-dependent demand, variable decaying rates, and partial backlogging while absolutely considering carbon emission costs. The model reflects practical market actions where demand initially increases and afterwards declines over time, and decay depends on the age of the item. To demonstrate the current model's applicability as well as evaluate the trade-off between …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Multi-directional Wind Turbine System Optimisation and Mathematical Modelling for India’s Sustainable Wind Energy Development
Abstract: The global trend towards green energy usage is expanding. Wind power is clean and sustainable and may compete with fossil fuels in the electricity market. This project's manufacturing cost must match fossil fuels or other energy sources to be competitive. The main investment in wind generation is in machinery and infrastructure. Wind power becomes competitive by lowering energy costs through turbine design, building, and operation. Understanding wind turbine activity over …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 1, Issue 1, 2023 · pp. 32–42 Read article
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Striking the Balance: Exploring the Interplay Between Quality and Cost in Modern Production Engineering
Abstract: This review paper examines the intricate and evolving relationship between quality and cost in the context of modern production engineering. In today's dynamic manufacturing landscape, the pursuit of excellence in product quality necessitates a strategic alignment with cost-effective methodologies, ensuring the sustainability and competitiveness of practices. This article serves as a comprehensive synthesis of current research, methodologies, and case studies, aiming to illuminate the dynamic interplay, challenges, and strategies adopted …
Published in International Journal of Industrial and Product Design Engineering · Vol. 1, Issue 2, 2023 · pp. 10–15 Read article
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In Silico Exploration of Podophyllum Hexandrum-Derived Phytocompounds as Potential Therapeutics Against Small Cell Lung Cancer (SCLC): A Molecular Docking Approach
Abstract: Small Cell Lung Cancer (SCLC) is a fast-growing and aggressive type of lung cancer that spreads quickly strongly associated with smoking. It is characterized by symptoms, such as persistent cough, breathing difficulties, or hoarseness, though it can sometimes be asymptomatic which makes early detection challenging. The tumor suppressor gene TP53 is critical in regulating the cell cycle and preventing uncontrolled cell division. Mutations in TP53 result in the loss of …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 1, 2025 · pp. 1–11 Read article
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Automation in Waste Management: How AI and Robotics Transforming Waste Sorting and Recycling
Abstract: Waste management is a big issue in the modern world, and it gets worse as urbanisation and industry increase. Hazards to the environment and human health result from traditional waste management practices' inability to effectively classify, recycle, and dispose of garbage. Robotics and artificial intelligence (AI) provide creative ways to improve trash processing, sorting, and collection. This article examines the application of robotics and artificial intelligence (AI) to waste management, …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
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Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article
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Future Challenges of Photocatalytic Water Splitting: Sustainability
Abstract: Photocatalytic water splitting has emerged as a promising technology for sustainable hydrogen production through the direct utilization of solar energy. This process mimics natural photosynthesis, using semiconductor materials to absorb light and drive the decomposition of water into hydrogen and oxygen. The method provides a sustainable and eco-friendly solution to the global energy challenge by enabling the reduction of carbon emissions. Among various solar-to-chemical energy conversion approaches, photocatalytic water splitting …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 43–48 Read article
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Experimental Validation and Implementation Framework for Optimized Methane Yield Prediction in Anaerobic Digestion
Abstract: The correct validation and realistic application of optimized anaerobic digestion (AD) models are essential steps in transferring biogas production systems to real-life. This paper outlines an experimental validation and deployment pipeline of an AI-optimized model of the methane yield prediction model based on the application of more advanced machine learning and Bayesian optimization methods. Others The validated surrogate-assisted optimization model was tested with controlled laboratory-scale AD experiments at optimized operating …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 25–32 Read article
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LQR-Based Optimal Control of Inverted Pendulum System with State Estimation and Stability Analysis
Abstract: The inverted pendulum on a cart is a canonical benchmark problem in control systems engineering, capturing the essential challenges of stabilizing an inherently unstable, underactuated, and nonlinear plant. Classical Proportional-Integral-Derivative (PID) controllers, while widely employed in industrial practice, exhibit fundamental performance limitations when applied to such systems, primarily due to their inability to account for multivariable coupling, process noise, and the absence of a systematic optimization framework. This paper presents …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 1, 2026 · pp. 31–43 Read article
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Solar Thermal Energy Utilization: Design Innovations and Performance Enhancement Techniques
Abstract: The utilization of solar thermal energy has become increasingly significant in the pursuit of sustainable and low-carbon energy solutions. Unlike photovoltaic technologies that directly convert sunlight into electricity, solar thermal systems focus on harnessing solar radiation to generate heat, which can then be applied to diverse sectors such as water heating, space conditioning, industrial process heating, and power generation. In recent years, substantial research efforts have been directed toward enhancing …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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Advancements in Nanostructured Membranes for Gas Separation: A Comprehensive Review
Abstract: Gas separation is vital in petrochemical, pharmaceutical, and environmental industries, yet traditional methods like distillation and cryogenic separation are energy-intensive and inefficient. Nanostructured membranes present a promising alternative, utilizing nanomaterials such as titanium dioxide, silica, carbon nanotubes, zeolite, and metal-organic frameworks to enhance separation efficiency and selectivity while reducing energy consumption. These membranes fall into various categories: polymeric nanostructured membranes, including mixed matrix and thin-film composites; inorganic membranes, such as …
Published in International Journal of Membranes · Vol. 1, Issue 1, 2024 · pp. 31–36 Read article
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DFT/Data Guided Predictive Modelling of Absorption Maxima in the OLED Rubrene Derivatives
Abstract: This study investigates the optical properties of rubrene derivatives to develop an accurate predictive model for absorption maxima using computational chemistry and chemoinformatic techniques. We benchmarked various quantum chemical methods, identifying that the M06-2X/aug-cc-pVDZ method in dichloromethane (DCM) provided the strongest correlation with experimental data. Key molecular descriptors such as band gap, ionization potential, and electrophilicity index were calculated and analyzed using principal component analysis (PCA) to identify significant factors …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 41–56 Read article