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نتیجه جستجو - Decomposition

تعداد مقالات یافته شده: 169
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1 Reconfiguration of electrical distribution network-based DG and capacitors allocations using artificial ecosystem optimizer: Practical case study
پیکربندی مجدد تخصیص DG و خازن مبتنی بر شبکه توزیع الکتریکی با استفاده از بهینه ساز اکوسیستم مصنوعی: مطالعه موردی عملی-2021
In this article, a new implementation of Artificial Ecosystem Optimizer (AEO) technique is developed for distributed generators (DGs) and capacitors allocation considering the Reconfiguration of Power Distribution Systems (RPDS). The AEO is inspired from three energy transfer mechanisms involving production, consumption, and decomposition in an ecosystem. In the production mechanism, the production operator allows AEO to produce a new individual randomly, whereas the search space exploration can be improved as illustrated in the consumption mechanism and exploitation can be performed in the decomposition. A practical case study of 59-bus Cairo distribution system in Egypt is simulated with different loading percentages. For optimizing the performance of that practical network, the AEO algorithm is employed for different scenarios. Besides, the results obtained by recent optimization techniques which are Jellyfish Search Optimizer (JFS), Supply Demand Optimizer (SDO), Crow Search Optimizer (CSO), Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA) are compared with the developed AEO. The simulation results demonstrate the efficacies and superiority of the AEO compared to the others. It surpasses the other algorithms in terms of obtaining the best, mean, worst, and standard deviations. After optimal RPDS and DGs placements, the power losses are decreased by 78.4, 77.84 and 71.4% at low, nominal and high levels, respectively. However, the best scenario with its application prospects is mentioned after optimal RPDS, DGs, and capacitors where the power losses are decreased by 68.8, 85.87 and 89.91% at low, nominal and high levels, respectively.
KEYWORDS: Artificial ecosystem optimizer | Distributed generators | Electrical systems | Power losses | Reconfiguration
مقاله انگلیسی
2 EBAPy: A Python framework for analyzing the factors that have an influence in the performance of EEG-based applications
EBAPy: یک چارچوب پایتون برای تجزیه و تحلیل عوامل موثر بر عملکرد برنامه های مبتنی بر EEG-2021
EBAPy is an easy-to-use Python framework intended to help in the development of EEG-based applications. It allows performing an in-depth analysis of factors that influence the performance of the system and its computational cost. These factors include recording time, decomposition level of Discrete Wavelet Transform, and classification algorithm. The ease-of-use and flexibility of the presented framework have allowed reducing the development time and evaluating new ideas in developing biometric systems using EEGs. Furthermore, different applications that classify EEG signals can use EBAPy because of the generality of its functions. These new applications will impact human–computer interaction in the near future.Code metadataCurrent code version v1.1Permanent link to code/repository used for this code version https://github.com/SoftwareImpacts/SIMPAC-2021-2Permanent link to Reproducible Capsule https://codeocean.com/capsule/4497139/tree/v1Legal Code License MITCode versioning system used gitSoftware code languages, tools, and services used Python Compilation requirements, operating environments & dependencies If available Link to developer documentation/manualSupport email for questions dustin.carrion@gmail.com
Keywords: EEG-based applications | Recording time | Discrete wavelet transform
مقاله انگلیسی
3 The optimal recovery-fund based strategy for uncertain supply chain disruptions: A risk-averse two-stage stochastic programming approach
استراتژی مبتنی بر صندوق بازیابی بهینه برای اختلالات نامشخص زنجیره تأمین: رویکرد برنامه ریزی تصادفی دو مرحله ای ریسک پذیر-2021
For a supply chain subject to uncertain production disruptions, the joint optimization of invest- ment intervention on recovery speed and duration of disrupted production capacity and location and inventory management has not been well studied. In this paper, a novel recovery strategy is introduced and studied, which uses investment to adjust the recovery speed and duration of production capacity, and two recovery behaviors responding to different types of disruptions are modeled. Considering uncertain disruption scenarios and their ripple effects over the supply chain, a risk-averse two-stage stochastic programming model (RTSPM) is established to study the integrated supply chain management of selection of distribution centers, multi-period inventory, transportation flows, and recovery-fund based mitigation policy. The RTSPM incorporates the risk preference of managers in decision making. We propose a trust-region-based decomposition method to solve the RTSPM and demonstrate its efficiency by benchmarking on state-of-the-art commercial solvers. Through numerical examples, we deeply analyze the effectiveness of RTSPM and the relations of optimal recovery investment decisions with the uncertain disruption factors. Finally, we provide implications and suggestions induced from the models and findings to aid the decisions on renting of distribution centers and the emergency investment and operational decisions when suffering the disruptions.
Keywords: Supply chain disruption management | Recovery-fund based mitigation strategy | Location-inventory-transportation model | Risk-averse two-stage stochastic programming | Trust-region-based decomposition method
مقاله انگلیسی
4 The effects of population aging on South Korea’s economy: The National Transfer Accounts approach
اثرات پیری جمعیت بر اقتصاد کره جنوبی: رویکرد حساب‌های انتقال ملی-2021
This study examines how two factors of population aging, changes in fertility and mortality, will respectively affect South Korea’s economic future. The economic effects of population aging are examined by considering the population in each age group under alternative demographic scenarios. Utilizing recent population projections and South Korea’s National Transfer Accounts, the paper applies a simple decomposition model measuring the respective effects of fertility and mortality on separate aspects of the economy: labor income, private and public consumption, and public and private transfers. The results show that the effects of low fertility and low mortality on the economy are very different in direction, magnitude, timing, and impact by age group. The only effect of an aging population that is the same in all circumstances is the effect on the public pension system: low fertility and mortality will increase pressure on the public pension system of South Korea.
keywords: پیری جمعیت | باروری کم | حساب های ملی انتقال | بحران پیری کره جنوبی | اقتصاد نسل | Population aging | Low fertility | National Transfer Accounts | South Korea’s aging crisis | Generational economy
مقاله انگلیسی
5 Making better decisions by applying mathematical optimization to cost accounting: An advanced approach to multi-level contribution margin accounting
تصمیم گیری های بهتر را با استفاده از بهینه سازی ریاضی به هزینه حسابداری: یک رویکرد پیشرفته به حسابداری حاشیه کمک چند سطح-2021
The purpose of multi-level contribution margin accounting in cost accounting is to analyze the profitability of products and organizational entities with appropriate allocation of fixed costs and to provide relevant information for short-term, medium- and longer-term decisions. However, the conventional framework of multi-level contribution margin accounting does not usually incorporate a mathematical optimization method that simultaneously integrates variable and fixed costs to determine the best possible product mix within hierarchically structured organizations. This may be surprising in that operations research provides an optimization model in the form of the fixed-charge problem (FCP) that takes into account not only variable costs but also fixed costs of the activities to be planned. This paper links the two approaches by expanding the FCP to a multi-level fixed-charge problem (MLFCP), which maps the hierarchical decomposition of fixed costs in accordance with multi-level contribution margin accounting. In this way, previously hidden optimization potentials can be made visible within the framework of multi-level contribution margin accounting. Applying the linkage to a case study illustrates that the original assessment of profitability gained on the sole basis of a multi-level contribution margin calculation might turn out to be inappropriate or even inverted as soon as mathematical optimization is utilized: products, divisions, and other reference objects for fixed cost allocation, which at first glance seem to be profitable (or unprofitable) might be revealed as actually unprofitable (or profitable), when the multi-level contribution margin calculation is linked to the MLFCP. Furthermore, the proposed concept facilitates assessment of the costs of an increasing variant diversity, which also demonstrates that common rules on how to interpret a multi-level contribution margin calculation may have to be revised in some cases from the viewpoint of optimization. Finally, the impact of changes in the fixed cost structure and other parameters is tested via sensitivity analyses and stochastic optimization.
keywords: حسابداری هزینه | حد مشارکت، محدوده مشارکت | هزینه های ثابت | نرم افزار | مخلوط محصول | تصمیم گیری | تحقیق در عملیات | مشکل ثابت شارژ | مشکل چند سطح قابل شارژ | بهینه سازی | برنامه نویسی صحیح | تجزیه و تحلیل میزان حساسیت | بهینه سازی تصادفی | صفحه گسترده | مطالعه موردی | Cost accounting | Contribution margin | Fixed costs | Profitability | Product mix | Decision making | Operations research | Fixed-charge problem | Multi-level fixed-charge problem | Optimization | Integer programming | Sensitivity analysis | Stochastic optimization | Spreadsheet | Case study
مقاله انگلیسی
6 Propagation of online consumer perceived negativity: Quantifying the effect of supply chain underperformance on passenger car sales
انتشار مصرف منفی مصرف کننده آنلاین: کمی کردن تأثیر کم عملکرد زنجیره تامین بر فروش خودروهای سواری-2021
The paper presents a text analytics framework that analyses online reviews to explore how consumer-perceived negativity corresponding to the supply chain propagates over time and how it affects car sales. In particular, the framework integrates aspect-level sentiment analysis using SentiWordNet, time-series decomposition, and bias- corrected least square dummy variable (LSDVc) – a panel data estimator. The framework facilitates the business community by providing a list of consumers’ contemporary interests in the form of frequently discussed product attributes; quantifying consumer-perceived performance of supply chain (SC) partners and comparing the competitors; and a model assessing various firms’ sales performance. The proposed framework demonstrated to the automobile supply chain using a review dataset received from a renowned car-portal in India. Our findings suggest that consumer-voiced negativity is maximum for dealers and minimum for manufacturing and assembly related features. Firm age, GDP, and review volume significantly influence car sales whereas the sentiments corresponding to SC partners do not. The proposed research framework can help the manufacturers in inspecting their SC partners; realising consumer-cited critical car sales influencers; and accurately predicting the sales, which in turn can help them in better production planning, supply chain management, marketing, and consumer relationships.
Keywords: Supply chain management | Sentiment analysis | Panel data modelling | Online reviews | Natural language processing
مقاله انگلیسی
7 Holistic cognitive conflict chain management framework in supply chain management
چارچوب جامع مدیریت زنجیره تعارض شناختی در مدیریت زنجیره تامین-2021
Closed-loop supply chains (CLSCs) have received considerable attention because of various economic and regulatory factors. A CLSC is characterized by more complicated network structures and higher uncertainties compared to traditional supply chain networks. Therefore, reliable CLSCs are being increasingly emphasized in academic circles due to the vast impacts of disruptions such as natural disasters and terrorist attacks. This paper studies a reliable location-inventory problem in a CLSC considering the mutual effects between failures of forward and reverse distribution centers (DCs) when they are co-located. The disruption probability of a co-located forward DC is different from that of a standalone forward DC, i.e., probabilistic disruptions are dependent on facility type. The problem is formulated as a nonconvex mixed-integer programming problem. A decomposition approach based on the outer approximation (DOA) algorithm is proposed to address the resulting model. The algorithm alternately solves relaxed master problems (mixed-integer linear programs, MILPs) and two nonlinear programming (NLPs) problems. Extensive numerical experiments are conducted to evaluate the performance of the proposed solution approach, after which managerial insights are explored.
Keywords: Closed-loop supply chain | Reliable location-inventory problem | Nonconvex optimization | Outer approximation
مقاله انگلیسی
8 Pricing and free periodic maintenance service decisions for an electric-and-fuel automotive supply chain using the total cost of ownership
قیمت گذاری و تصمیمات خدمات تعمیر و نگهداری دوره ای رایگان برای یک زنجیره تامین خودروی الکتریکی و سوختی با استفاده از کل هزینه مالکیت-2021
Although subsidies have had significant impacts on the electric vehicle (EV) market share, many governments have planned to eliminate subsidies. There is a concern that unsubsidized EVs reduce the EV market share, significantly. However, purchasing an EV instead of a fuel vehicle (FV) might impose a lower total cost of ownership (TCO) on customers, depending on their vehicle usage. In this case, supply chains could optimize their decisions considering which vehicle is affordable for each customer class from the view of TCO. This study investigates optimal pricing and free periodic maintenance service (FPMS) decisions in a two-stage electric-and- fuel automotive supply chain, considering TCO to estimate vehicle market shares under customer classification with different vehicle usage patterns. Two bi-level models are developed and solved through Karush-Kuhn- Tucker equations and a reformulation-and-decomposition algorithm. Sensitivity analyses are performed considering various scenarios on energy prices and ownership periods. Results indicate that the high-usage customers are more likely to purchase an EV if the ownership period is the same for all classes. However, if low-usage customers keep the vehicle for a longer period than the others, they are more likely to purchase an EV. Both providing FPMSs by the manufacturer instead of the retailer and increasing the fuel price over time with a higher rate, compared with the electricity price and the inflation rate, improve the EV market share and reduce the total fuel consumption and emissions. Investment to produce EVs is not economical for a high price of electricity while having low fuel prices.
Keywords: Electric vehicles | Total cost of ownership | Automotive supply chain | Pricing decision | Bi-level programming | Decomposition algorithm
مقاله انگلیسی
9 012-S00304018210
012-S00304018210-2021
A novel multiple-single-channel color image cryptosystem based on unequal spectrum decomposition (USD) and 2D sine improved 1ogistic iterative chaotic map with infinite collapse modulation map (2D-SLIM) is proposed. In this method, R, G, and B channels of each color image of an authorized user is fused with corresponding LL sub-band of a gray-scale carrier image by inverse discrete wavelet transform (DWT) to obtain single-channel and watermarked image. The individual biometric key of an authorized user is produced by his/her phase- encoded irisprint and then modulated by chaotic random phase mask (CRPM). So the parameters of CRPM are used as decryption keys with the uniqueness of the irisprint. The watermarked image as input image is normalized, multiplied with biometric key, and then Fresnel transformed. The Fresnel spectrum is divided into two complex-value masks by using unequal spectrum decomposition in which one phase mask is exploited as decryption key and other as ciphertext. The final ciphertext is obtained by adding individual ciphertexts. The encryption and decryption process can be realized with a hybrid optoelectronic system. Numerical simulations have been performed to verify the validity and feasibility of the proposed system.
Keywords: 2D-SLIM | Unequal spectrum decomposition | Biometric keys
مقاله انگلیسی
10 A Study on the Optimal Inventory Allocation for Clinical Trial Supply Chains
یک مطالعه در مورد اختصاص مطلوب موجودی برای زنجیره های تأمین کارآزمایی بالینی-2021
With increasing competition in the pharmaceutical industry, pharmaceutical companies pay more attention to improving the efficiency of clinical trial supply chains to reduce the drug supplying cost, which takes up a considerable part of the total research and development expense. To improve the efficiency of clinical trial supply chains, this study investigates the inventory levels of clinical drugs in each period at a distribution center and clinics considering the reverse replenishment, transshipment, and generalized stockout cost. The inventory allocation problem in clinical trial supply chains is formulated as a rolling horizon-based two-stage stochastic mixed-integer model where the minimal operational cost constitutes the underage cost at the production planning level of clinical trial supply chains. An algorithm extending Benders decomposition is proposed as the solution approach. We also derive several structural results and develop the reformulation method and row generation strategy to improve the efficiency of the optimization process. The effectiveness of our approach is demonstrated in the numerical experiment.
Keywords: Supply chain management | Clinical trials | Inventory allocation | Stochastic programming
مقاله انگلیسی
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