Optimizing the Economic Order Quantity Using Fuzzy Theory and Machine Learning Applied to a Pharmaceutical Framework

Mathematics, Journal Year: 2024, Volume and Issue: 12(6), P. 819 - 819

Published: March 11, 2024

In this article, we present a novel methodology for inventory management in the pharmaceutical industry, considering nature of its supply chain. Traditional models often fail to capture particularities sector, characterized by limited storage space, product degradation, and trade credits. To address these particularities, using fuzzy logic, propose that are adaptable real-world scenarios. The proposed designed reduce total costs both vendors clients, gap not explored existing literature. Our employs pentagonal number (PFN) arithmetic Kuhn–Tucker optimization. Additionally, integration naive Bayes (NB) classifier use Weka artificial intelligence suite increase effectiveness our model complex decision-making environments. A key finding is high classification accuracy model, with NB correctly categorizing approximately 95.9% scenarios, indicating an operational efficiency. This complemented capability determine optimal production quantity, cost factors related manufacturing transportation, which essential minimizing overall costs. methodology, based on machine learning enhances dynamic sectors like industry. While focus single-product scenario between suppliers buyers, future research hopes extend wider contexts, as epidemic conditions other applications.

Language: Английский

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Efficiency, optimality, and selection in a rigid actuation system with matching capabilities for an assistive robotic exoskeleton

Engineering Science and Technology an International Journal, Journal Year: 2024, Volume and Issue: 51, P. 101613 - 101613

Published: Feb. 8, 2024

Selecting the right actuator for a portable exoskeleton involves comprehensive evaluation of various design characteristics. In this study, we introduce methodology selection based on specific tasks, enhancing practical adoption exoskeletons. By examining range candidate actuators designed lower limb exoskeletons, our objective is to engineer system that both lightweight and power-efficient. These actuators, developed by integrating diverse motors transmission systems, were rigorously tested against defined tasks. Our methodology, applied an assistive catered elderly, showed its potential in tailoring efficient with matching capabilities. The obtained results indicated ideal configuration achieved reductions weight power requirements 35% 80%, respectively. present research delineates strategic approach contributing evolution high-performing devices.

Language: Английский

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Modeling Residential Energy Consumption Patterns with Machine Learning Methods Based on a Case Study in Brazil

Mathematics, Journal Year: 2024, Volume and Issue: 12(13), P. 1961 - 1961

Published: June 25, 2024

Developing efficient energy conservation and strategies is relevant in the context of climate change rising demands. The objective this study to model predict electrical power consumption patterns Brazilian households, considering thresholds for use. Our methodology utilizes advanced machine learning methods, such as agglomerative hierarchical clustering, k-means self-organizing maps, identify patterns. Gradient boosting, chosen its robustness accuracy, used a benchmark evaluate performance these methods. reveals from perspectives both users providers, assessing corresponding effectiveness according stakeholder needs. Consequently, provides comprehensive empirical framework that supports strategic decision making management consumption. findings demonstrate clustering outperforms other offering more precise classification This finding aids development targeted policies enhances resource strategies. present research shows applicability analytical methods specific contexts, showing their potential shape future practices.

Language: Английский

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A Hybrid Fuzzy Mathematical Programming Approach for Manufacturing Inventory Models with Partial Trade Credit Policy and Reliability

Axioms, Journal Year: 2024, Volume and Issue: 13(11), P. 743 - 743

Published: Oct. 29, 2024

This study introduces an inventory model for manufacturing that prioritizes product quality and cost efficiency. Utilizing fuzzy logic mathematical programming, the integrates numbers to describe uncertainties associated with costs control parameters. The extends beyond conventional systems by incorporating a dynamic mechanism halt production, employing decision variables optimize economic order quantity minimize total costs. Key innovations include application of approaches related graded mean integration defuzzification use Kuhn–Tucker conditions ensure optimal solutions under complex constraints. These facilitate precise management production rates, levels, factors, which are essential in achieving balance between supply demand. A computational analysis validates model’s effectiveness, demonstrating reductions while maintaining levels. underscores potential integrating arithmetic traditional optimization techniques enhance making management. adaptability accuracy indicate its broad applicability across various sectors facing similar challenges, offering valuable tool operational managers makers improve efficiency reduce waste cycles.

Language: Английский

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