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نتیجه جستجو - Simulation model

تعداد مقالات یافته شده: 63
ردیف عنوان نوع
1 Data Mining Strategies for Real-Time Control in New York City
استراتژی داده کاوی برای کنترل زمان واقعی در شهر نیویورک-2105
The Data Mining System (DMS) at New York City Department of Transportation (NYCDOT) mainly consists of four database systems for traffic and pedestrian/bicycle volumes, crash data, and signal timing plans as well as the Midtown in Motion (MIM) systems which are used as part of the NYCDOT Intelligent Transportation System (ITS) infrastructure. These database and control systems are operated by different units at NYCDOT as an independent database or operation system. New York City experiences heavy traffic volumes, pedestrians and cyclists in each Central Business District (CBD) area and along key arterial systems. There are consistent and urgent needs in New York City for real-time control to improve mobility and safety for all users of the street networks, and to provide a timely response and management of random incidents. Therefore, it is necessary to develop an integrated DMS for effective real-time control and active transportation management (ATM) in New York City. This paper will present new strategies for New York City suggesting the development of efficient and cost-effective DMS, involving: 1) use of new technology applications such as tablets and smartphone with Global Positioning System (GPS) and wireless communication features for data collection and reduction; 2) interface development among existing database and control systems; and 3) integrated DMS deployment with macroscopic and mesoscopic simulation models in Manhattan. This study paper also suggests a complete data mining process for real-time control with traditional static data, current real timing data from loop detectors, microwave sensors, and video cameras, and new real-time data using the GPS data. GPS data, including using taxi and bus GPS information, and smartphone applications can be obtained in all weather conditions and during anytime of the day. GPS data and smartphone application in NYCDOT DMS is discussed herein as a new concept. © 2014 The Authors. Published by Elsevier B.V. Selection and peer-review under responsibility of Elhadi M. Shakshu Keywords: Data Mining System (DMS), New York City, real-time control, active transportation management (ATM), GPS data
مقاله انگلیسی
2 An exploration of local rules to map spawning processes to regular hardware architectures
کاوشی در قوانین محلی برای نگاشت فرآیندهای تخم ریزی به معماری های سخت افزاری معمولی-2022
This thesis presents an exploration of population growth via simulation in software to ascertain if a massively parallel hardware system can manage applications running within. Task execution happens dynamically and is controlled by the growth mechanism implementing efficient mapping in simulation. Algorithms that provide population simulation models are often inspired by those evidenced in biology and in particular those of cellular automata and L-systems. These algorithms are of particular interest due to their complexity and self-replication and recent research has shown that it is the refinement of the biological methodology that has resulted in their complexity. Further to this, adaptation of the design has moved the algorithm on towards being able to organize and build itself from a single cell. A growth model is utilized in software systems to provide production of meaningful data. The development of bio-inspired software is constrained by using contemporary processor architectures.
مقاله انگلیسی
3 Supply- and cyber-related disruptions in cloud supply chain firms: Determining the best recovery speeds
اختلالات مربوط به تأمین و سایبر در شرکت های زنجیره تامین ابر: تعیین بهترین سرعت بازیابی-2021
This study investigated the speeds (i.e., radical, incremental, relaxed benchmarking, rigorous benchmarking, matching, and market-driven) of firms’ recovery from supply- and cyber-related disruptions in cloud supply chains (SCs). Supply-related disruptions downgrade the firm’s operational capabilities (e.g., production capacity and labor supply), and cyber-related disruptions reduce its intangible capabilities (e.g., reputation, brand image, and public trust). This study introduced a cellular automata (CA) simulation model to determine the best recovery speeds following the loss of operational and intangible capabilities. Furthermore, to investigate the impact of cloud adoption on an SC firm’s best speeds of recovery from supply-related disruptions, we compared firms that had adopted the cloud with those using the on-site data centers.
Keywords: Supply chain | Cloud computing | Disruption | Recovery | Cellular automata simulation
مقاله انگلیسی
4 Comparison between centralized and decentralized supply chains of autologous chimeric antigen receptor T-cell therapies: a UK case study based on discrete event simulation
مقایسه بین زنجیره های تأمین متمرکز و غیرمتمرکز درمان سلول های T گیرنده آنتی ژن کایمریک اتولوگ: یک مطالعه موردی در انگلیس بر اساس شبیه سازی رویداد گسسته-2021
Background aims: Decentralized, or distributed, manufacturing that takes place close to the point of care has been a manufacturing paradigm of heightened interest within the cell therapy domain because of the product’s being living cell material as well as the need for a highly monitored and temperature-controlled supply chain that has the potential to benefit from close proximity between manufacturing and application. Methods: To compare the operational feasibility and cost implications of manufacturing autologous chimeric anti- gen receptor T (CAR T)-cell products between centralized and decentralized schemes, a discrete event simulation model was built using ExtendSIM 9 for simulating the patient-to-patient supply chain, from the collection of patient cells to the final administration of CAR T therapy in hospitals. Simulations were carried out for hypothetical systems in the UK using three demand levels—low (100 patients per annum), anticipated (200 patients per annum) and high (500 patients per annum)—to assess resource allocation, cost per treatment and system resilience to demand changes and to quantify the risks of mix-ups within the supply chain for the delivery of CAR T treatments. Results: The simulation results show that although centralized manufacturing offers better economies of scale, individual facilities in a decentralized system can spread facility costs across a greater number of treatments and better utilize resources at high demand levels (annual demand of 500 patients), allowing for an overall more comparable cost per treatment. In general, raw material and consumable costs have been shown to be one of the greatest cost drivers, and genetic modification-associated costs have been shown to account for over one third of raw material and consumable costs. Turnaround time per treatment for the decentralized scheme is shown to be consistently lower than its centralized counterpart, as there is no need for product freeze-thaw, packaging and transportation, although the time savings is shown to be insignificant in the UK case study because of its rather compact geographical setting with well-established transportation networks. In both schemes, sterility testing lies on the critical path for treatment delivery and is shown to be critical for treatment turnaround time reduction. Conclusions: Considering both cost and treatment turnaround time, point-of-care manufacturing within the UK does not show great advantages over centralized manufacturing. However, further simulations using this model can be used to understand the feasibility of decentralized manufacturing in a larger geographical setting.© 2020 International Society for Cell & Gene Therapy. Published by Elsevier Inc. All rights reserved.
Key Words: CAR T | centralization | decentralization | discrete event simulation | manufacturing | supply chain
مقاله انگلیسی
5 Technical-knowledge-integrated material flow cost accounting model for energy reduction in industrial wastewater treatment
مدل حسابداری مواد مخدر فنی دانش فنی برای کاهش انرژی در درمان فاضلاب صنعتی-2021
A novel simulation model incorporating the concept of material flow cost accounting (MFCA) into a numerical process simulator for wastewater treatment plants (WWTPs) was developed. Cost-related parameters, such as electrical power consumption, were calculated for each unit process by referring to predetermined formulas of design rules and technical knowledge built into the model. These calculated values were then assigned to the outflow stream proportional to the flowrate, allowing each flow stream in the WWTP to be quantified according to the history of assigned costs. This method increased the number of quantity centers in MFCA models regardless of actual data availability, thus contributing complex flow configuration and flexible comparison of improvement approaches related to financial evaluation. Energy cost allocation maps created by this model demonstrated the benefits of anaerobic treatment in the WWTP of a soft-drink factory in Japan. Additionally in this WWTP, the observed values of total power consumption were 40% higher than the simulated values, and improvement approaches, such as instrumental control of aeration, were evaluated for their feasibility and financial impact. These results demonstrated the success of the model in adding and reinforcing analytical and predictive functions in the MFCA survey method.
Keywords: Material flow cost accounting | Process simulation model | Industrial wastewater | Energy saving | Food and beverage industry
مقاله انگلیسی
6 یک مدل برای شبیه‌سازی و طرح‌ریزی پویای مسیر تعویض باند مبتنی بر تابع پارامتری جدید
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 16 - تعداد صفحات فایل doc فارسی: 22
مسأله‌ی تعویض باند (LC) می‌تواند موجب تصادفات شدید شده و ترافیک آزاردهنده‌ای را در جاده‌های چندبانده ایجاد نماید. مدل موجود برای شبیه‌سازی LC با یک سری محدودیت‌ها (انطباق کم، فقدان مشخصه‌های سرعت و شتاب، انحنای زیاد) با استفاده از منحنی مسیرهای شناخته‌شده‌ای همچون منحنی مماس هایپربولیک (HTC)، منحنی مبتنی بر سینوس (SC)، و منحنی چندجمله‌ای (PC) ایجاد شد. در این مقاله، یک منحنی پارامتری جدید با استفاده از دستگاه مختصات خمیده‌خطی ارائه و با پایگاه داده‌ی واقعی شبیه‌سازی نسل آتی (NGSIM) انطباق داده شد. سپس مشخصه‌های جدید سرعت و شتاب با استفاده از منحنی مسیر LC پیشنهاد شدند. انحنای مدل پیشنهادی در هر دو نقطه‌ی آغاز و پایان LC، انحنای مبتنی بر صفر بود. این انحنای پیشنهادی با دو مدل همانند HTC و SC مقایسه شد. خطای متوسط جذر میانگین مربعات مدل پیشنهادی در مقایسه با مدل HTC، برای LC چپ به میزان 1.84% و برای LC راست به میزان 15.48% و در مقایسه با مدل SC به میزان 1.74% برای LC چپ و به میزان 15.60% برای LC راست کاهش می‌یابد. بطور مشابه، مدل پیشنهادی برای مشخصه‌های سرعت و شتاب نسبت به مدل PC تا حد زیادی بهبود می‌یابد. منحنی پارامتری پیشنهادی، نقاط فاصله و برخورد خودروی LC با یک خودروی جلویی و خودروی پشتی در باند هدف را حل می‌کند و می‌توان از آن در برنامه‌ریزی مسیر LC واقعی استفاده کرد.
کلیدواژه ها: مشخصه‌های شتاب | منحنی پارامتری | سرعت | برنامه‌ریزی مسیر
مقاله ترجمه شده
7 Hybrid simulation models for spare parts supply chain considering 3D printing capabilities
مدل های شبیه سازی ترکیبی برای زنجیره تامین قطعات یدکی با توجه به قابلیت های چاپ سه بعدی-2021
In the era of Industry 4.0, 3D printing unlocks a wide array of solutions to rapidly-produce spare parts for maintenance operations. In this research, we propose a hybrid simulation approach, combining agent-based and discrete event simulation methods, to investigate how the adoption of 3D printing technologies to manufacture spare parts for maintenance operations will improve operational efficiency and effectiveness. Specifically, our framework is applied to the United States Navy’s fighter jet maintenance operations to study various network configurations, where 3D printing facilities may be centralized, decentralized, or hub configured. System performance in terms of the total cost, timeliness of delivery, and vulnerability under disruptions such as cyber- attacks and emergencies are evaluated. Lastly, the impact of 3D printing technological advancements on operational performance is investigated to obtain managerial insights.
Keywords: 3D printing | Hybrid simulation | Maintenance operations | Supply chain network configuration
مقاله انگلیسی
8 Dynamic simulation modelling of software requirements change management system
مدل سازی شبیه سازی پویا سیستم مدیریت تغییر نیازمندی های نرم افزاری-2021
Changes in the Software requirements, technological advances require flexibility in software system develop- ment. Unexpected changes and mistakes cause difficulties. They effectively manage destructive changes, rework, and errors; project managers need to consider dynamic behavior loops of feedback on lead delays and distur- bances. System Dynamics (SD) modeling methods have been used in the last few decades to meet this demand for analytical and project performance improvement. The SD model is used to improve the simulated change management policy for the Iranian project in the project’s planning and petrochemical industry. Dynamic simulations of the SD model. The results show that effective Knowledge Management (KM) is a crucial control factor for the project’s mechanically essential controls. Therefore, the proposal on the Knowledge Management aspect and attempts are to improve the manufacturing industry model. Effective formulation of dynamic simulation models project change management policy, time, consider Cost, quality, resources, and financial indicators. This model, such as financing, outsourcing activities, adjustment of the schedule, labor management, etc., to compare the alternative change management strategy in terms of the project’s performance indicators to enable the decision-makers.
keywords: مدیریت دانش | پویایی سیستم (SD) | هزینه | کیفیت | منابع | Knowledge management (km) | System dynamics (sd) | Cost | quality | resources
مقاله انگلیسی
9 Impacts of variable interest rates on the market areas of a spatial duopoly in supply chains operating on the finite horizon
تأثیر نرخ بهره متغیر در مناطق بازار از یک دوگانگی فضایی در زنجیره های تأمین موجود در افق محدود-2021
The paper aims to present a theoretical study of inventory allocation in two retailer warehouses that form a spatial duopoly on the finite horizon, where the shortage of goods, and not only prices, determines their market areas, depending on the customer’s travel decisions to minimise not only the cost of purchasing the items but also the travel expenses under uncertainties of availability of the products. The customers’ decision on which store to visit first is influenced by their estimation of regarding shortages of goods. The demand size required by arrived customers can be one or more units of goods. Delays in the required amount and all flows in the pro- duction–inventory–logistic system have varying parameters, simulated by the Network Simulation Method (NSM). The impact of delay in supply chain, which provides the products and consequently creates the shortages on market areas, is studied at varying interest rates and the shortened, unknown length of the time horizon. The annuity stream approach of evaluation of ordering policies is applied in areas of spatial duopoly where the optimal ordering policy depends on the interaction between the prices and the shortages of goods in the studied duopolies. Customer travelling problem (CTP) is defined, which determines the market area for allocated inventories. In our study, various distributions of customers’ quantity demand at varying shortages and delays of the provision are supposed, presenting their impact on the market area. NSM helps in describing how to study the impact of varying interest rates and stochastic length of the time horizon in the case of shortages of goods as a consequence of delays in supply system activities and how to improve the estimates of NPV and profit in the case of low and varying interest rates.
Keywords: Location | Inventory | Network simulation model | MRP theory | Annuity stream | Duopoly | Customer travelling problem | Stochastic horizon
مقاله انگلیسی
10 Transformation of semantic knowledge into simulation-based decision support
تحول دانش معنایی به پشتیبانی تصمیم گیری مبتنی بر شبیه سازی-2021
Simulation is capable to cope with the uncertain and dynamic nature of industrial value chains. However, indepth system expertise is inevitable for mapping objects and constraints from the real world to a virtual model. This knowledge-intensity leads to long development times of respective projects, which contradicts the need for timely decision support. Since more and more companies use industrial knowledge graphs and ontologies to foster their knowledge management, this paper proposes a framework on how to efficiently derive a simulation model from such semantic knowledge bases. As part of the approach, a novel Simulation Ontology provides a standardized meta-model for hybrid simulations. Its instantiation enables the user to come up with a fully parameterized formal simulation model. Newly developed Mapping Rules facilitate this process by providing guidance on how to turn knowledge from existing ontologies, which describe the system to be simulated, into instances of the Simulation Ontology. The framework is completed by a parsing procedure for an automated transformation of this conceptual model into an executable one. This novel modeling approach makes model development more efficient by reducing its complexity. It is validated in a use case implementation from semiconductor manufacturing, where cross-domain knowledge was required in order to model and simulate the impacts of the COVID-19 pandemic on a global supply chain network.
keywords: تحول دانش | پشتیبانی تصمیم | هستی شناسی | مدل سازی ترکیبی | شبیه سازی همه گیر | شبیه سازی زنجیره تامین | Knowledge Transformation | Decision Support | Ontologies | Hybrid modeling | Pandemic Simulation | Supply chain simulation
مقاله انگلیسی
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