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یک مدل ریاضی چند منظوره برای زنجیره تامین داروسازی با توجه به تراکم دارو در کارخانهها
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 15 - تعداد صفحات فایل doc فارسی: 47 مدیریت زنجیره تامین ( SCM ) , به روش یکی از مسائل مهم در جنبه مدیریتی , نقش مهمی در مقابله با مسایل انسانی و مشکلات ایفا میکند . به دلیل برخی محدودیتها ( به عنوان مثال , ظرفیت تولید و ظرفیت ذخیرهسازی ) و خواسته ها( به عنوان مثال , کاهش هزینه و افزایش درآمد ) , مدیران زنجیره تامین همیشه به دنبال بهترین پاسخ به مقدار و نوع ارتباط بین سطوح مختلف SCM هستند . در تحقیقات آتی , یک زنجیره تامین دارو ( PSC ) با سه تابع هدف توسعهیافته , با هدف به حداقل رساندن هزینههای کلی , خواستههای برآورده نشده , و کاهش زمان انتظار در ورودی کارخانه . در تحقیقات آتی , موضوع کلی و تحقیقات در مدلسازی PSC و حل مساله مورد بحث قرار گرفتهاند . سپس یک مدل برنامهریزی غیرخطی با تحقیقات قبلی برای حل کاستیهای موجود پیشنهاد شدهاست.
همچنین روشهای تصمیمگیری چند هدفه برای انطباق با اهداف متناقض مدل به طور همزمان استفاده میشوند . سپس نرمافزار تجاری GAMS برای حل مشکل اندازههای مختلف به کار میرود . در نهایت ، تحلیل حساسیت گسترده و ارزیابی نتایج مورد بحث قرار میگیرد و پیشنهادهای توسعه آتی ارایه میشوند. واژه های کاربردی : زنجیره تامین دارو | فسادپذیری | زمانبندی | فهرست | نظریه کیوینگ |
مقاله ترجمه شده |
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Roles of gender, study major, and origins in accounting learning: A case in Thailand
نقش جنسیت، مطالعه اصلی و ریشه های یادگیری حسابداری: مورد در تایلند-2021 Management students are required to pass several quantitative subjects, such as Accounting,
Business Finance, and Mathematics, during their study at the undergraduate level. There are
limited studies conducted in Thailand that explored students’ learning achievement in accounting
courses. This paper explored the learning achievement of undergraduate management students in
the introductory accounting course at a public university in Thailand. It examined whether the
achievement differs across the students’ gender, study major, and origins. Data from 906 man-
agement students were taken as samples. This study relied on the independent samples t-test and
one-way ANOVA to analyze the data. The results suggested that the performance of undergrad-
uate management students in the accounting course differs significantly across genders, majors,
and origins of the students. keywords: عملکرد یادگیری | دانش آموزان مدیریت | آموزش حسابداری | جنسیت | مطالعه اصلی | ریشه | Learning performance | Management students | Accounting education | Gender | Study major | Origins |
مقاله انگلیسی |
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Accounting-based downside risk and stock price crash risk: Evidence from China
ریسک نزولی مبتنی بر حسابداری و خطر سقوط قیمت سهام: شواهدی از چین-2021 In the past 15 years, an emerging literature has extensively studied individual stock price crash risk, which refers to the likelihood
of an abrupt and large-scale drop in stock prices (e.g., Chen et al., 2001; Hutton et al., 2009; Jin and Myers 2006; Kim et al., 2011a, Li
and Zhang 2011b; Kim and Zhang 2016). An important strand of this literature focuses on the Chinese emerging markets where,
arguably, the extent of “bad news hoarding” is severer compared to developed markets due to China’s less effective corporate
governance environment (Wang et al., 2020). In this paper, we examine the relationship between accounting-based downside risk and
stock price crash risk using a large sample of Chinese listed firms.
The contribution of this study lies in a recently developed indicator of earnings fundamentals that is, arguably, more consistent with
“bad news hoarding”: accounting-based downside risk, hereafter denoted as ABDR. Studies have shown that investors care more about
downside losses than upside gain potentials and are therefore more sensitive to losses than to gains (e.g., Gul 1991; Kahneman and
Tversky 1979). Accordingly, Koonce et al. (2005) show that economic agents judge negative and positive expectations differently in
risk management, placing more emphasis on potential loss outcomes. However, earnings volatility and other existing accounting-based
downside risk measures consist of both downside and upside variabilities with equal weights and little research has examined the
downside risk of accounting-based measures. Konchitchki et al. (2016) are the first to construct measures of accounting-based
downside risk and examine its pricing implications in U.S. markets. In particular, this study uses the relative root lower partial
moment as a mathematical foundation to capture exposure to downside risk rather than the overall volatility. Accounting-based
downside risk measures focus on the below-expectation variability in firm performance measures, particularly return-on-assets (ROA).
We extend Konchitchki et al. (2016) by performing an investigation in the Chinese markets. Furthermore, we examine the variation keywords: Accounting-based downside risk | Stock price crash risk | Bad-news hoarding, China | ریسک نزولی مبتنی بر حسابداری | ریسک سقوط قیمت سهام | احتکار اخبار بد، چین |
مقاله انگلیسی |
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Accounting for cross-immunity can improve forecast accuracy during influenza epidemics
حسابداری برای مصونیت متقابل می تواند دقت پیش بینی را در طول اپیدمی های آنفلوانزا بهبود بخشد-2021 Previous exposure to influenza viruses confers cross-immunity against future infections with related strains.
However, this is not always accounted for explicitly in mathematical models used for forecasting during
influenza outbreaks. We show that, if an influenza outbreak is due to a strain that is similar to one that
has emerged previously, then accounting for cross-immunity explicitly can improve the accuracy of real-time
forecasts. To do this, we consider two infectious disease outbreak forecasting models. In the first (the ‘‘1-group
model’’), all individuals are assumed to be identical and cross-immunity is not accounted for. In the second
(the ‘‘2-group model’’), individuals who have previously been infected by a related strain are assumed to
be less likely to experience severe disease, and therefore recover more quickly, than immunologically naive
individuals. We fit both models to estimated case notification data (including symptomatic individuals as
well as laboratory-confirmed cases) from Japan from the 2009 H1N1 influenza pandemic, and then generate
synthetic data for a future outbreak by assuming that the 2-group model represents the epidemiology of
influenza infections more accurately. We use the 1-group model (as well as the 2-group model for comparison)
to generate forecasts that would be obtained in real-time as the future outbreak is ongoing, using parameter
values estimated from the 2009 epidemic as informative priors, motivated by the fact that without using prior
information from 2009, the forecasts are highly uncertain. In the scenario that we consider, the 1-group model
only produces accurate outbreak forecasts once the peak of the epidemic has passed, even when the values
of important epidemiological parameters such as the lengths of the mean incubation and infectious periods
are known exactly. As a result, it is necessary to use the more epidemiologically realistic 2-group model to
generate accurate forecasts. Accounting for cross-immunity driven by exposures in previous outbreaks explicitly
is expected to improve the accuracy of epidemiological modelling forecasts during influenza outbreaks.
keywords: مدلسازی ریاضی | پیش بینی آنفلوانزا | Real-timeForecast | مصونیت متقابل | 2009 H1N1 پاندمی | Mathematicalmodelling | Influenzaforecasting | Real-timeforecast | Cross-immunity | 2009H1N1pandemic |
مقاله انگلیسی |
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Biomass supply chain coordination for remote communities: A game-theoretic modeling and analysis approach
هماهنگی زنجیره تأمین زیست توده برای جوامع از راه دور: رویکرد مدل سازی و تحلیل نظری بازی-2021 Biomass, as one of the most available renewable energies, could reduce dependency on fossil fuels and the consequent environmental impacts. There is a need for biomass supply chain management, which is managing bioenergy production from harvesting feedstock to energy conversion facilities. In case of remote communities, bioenergy adoption requires dealing with dispersed geographies of suppliers and places of consumption with small scales of energy demand. As such, coordination plays a key role in increasing the efficiency of the biomass supply chain network through bundling of demand and thus improving the economy of scale. This paper employs a game-theoretic approach to formulate a coordinated biomass supply chain with three echelons including suppliers, hubs, and energy convertors. To investigate the strategic interactions of participants, three decision making structure scenarios have been considered under Stackelberg game providing insights into the impact of power distribution, the role of side payments in enforcing the flow of decisions, and the resulting efficiency and performance improvements. In doing so, a case study bioenergy supply chain for three northern Canadian communities is explored to demonstrate the application of the proposed formulation, solution methods, and the practicality and significance of the adopted approach and outcomes for remote communities. Keywords: Bioenergy | Supply chains | Coordination | Remote communities | Game theory | Mathematical Program with Equilibrium | Constraints (MPEC) |
مقاله انگلیسی |
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Innovation for sustainability in the Global South: bibliometric findings from management & business and STEM (science, technology, engineering and mathematics) fields in developing countries
نوآوری برای پایداری در جنوب جهانی: یافته های کتاب سنجی از مدیریت و تجارت و زمینه های STEM (علم، فناوری، مهندسی و ریاضیات) در کشورهای در حال توسعه-2021 Research on innovation and sustainability is prolific but fragmented. This study integrates the research on
innovation in management and business and STEM fields for sustainability in a unified framework for the case of
developing countries (i.e., the Global South). It presents and discusses the output, impact, and structure of such
research based on a sample of 14,000 þ articles and conference proceedings extracted from the bibliographic
database Scopus. The findings reveal research output inflections after global announcements such as UN-Earth
Summits. The study also reveals the indisputable leadership of China in overall output and research agendasetting.
Nonetheless, countries such as India, Mexico, and Nigeria are either more efficient or impactful. GS
research published in highly reputable journals is still scarce but increasing modestly. Central topic clusters (e.g.,
knowledge management) remain peripheral to the global Sustainable Development Goals (SDGs) research landscape.
Finally, academic-corporate collaboration is in its infancy and limited to particular economic sectors:
energy, pharmaceuticals, and high-tech.
keywords: نوآوری | پایداری | مدیریت | کشورهای در حال توسعه | اتصال کتابشناختی | Innovation | Sustainability | Management | STEM | Developing countries | Bibliographic coupling |
مقاله انگلیسی |
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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 |
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Optimization of extended business processes in digital supply chains using mathematical programming
بهینه سازی فرآیندهای تجاری گسترده در زنجیره های تأمین دیجیتال با استفاده از برنامه ریزی ریاضی-2021 We propose a mathematical programming approach to optimize the business process transactions in digital supply chains. Five scheduling models from the Process Systems Engineering (PSE) area are applied
to schedule the processing of orders in a simplified Order-To-Cash (OTC) business process, which is modeled as a multistage network with parallel units (agents). Two case studies are presented to compare the
performance of the scheduling models on various sizes of a flexible jobshop representation of the OTC
process. The models are compared and scaled to select those that are more suitable to this application.
The continuous-time general precedence model provides an accurate representation of the real system
and performs well for small instances. The discrete-time State-Task Network (STN), however, proves most
efficient in terms of tractability, despite the well-known limitations resulting from discretizing time. The
tightness of the linear programming (LP) relaxations in the discrete-time STN framework, as well as the
ability of commercial solvers to perform preprocessing and apply heuristics to the STN formulation, enables finding near optimal solutions quickly even for larger instances. Keywords: Business process optimization | digital supply chain | order-to-cash | scheduling | mathematical programming |
مقاله انگلیسی |
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Quantitative study of starch swelling capacity during gelatinization with an efficient automatic segmentation methodology
Quantitative study of starch swelling capacity during gelatinization with an efficient automatic segmentation methodology-2021 A novel image segmentation methodology combined with optical microscopy observation was developed for qualifying starch swelling. Starch granules in the micrograph were successfully segmented based on high- precision edges extraction achieved by Canny edge detection together with mathematical morphology operation. Granules were automatically identified by computer vision and characterized by giving quantifiable area of these granules. The evolved swelling process could be generally divided into two phases. During the first phase, starch granules were only swollen up by 2.56 %, which is hard to be identified by conventional naked eye. During the following narrow temperature interval (60–66 ℃), these starch granules were detected to swell up significantly by 9.08 %. Through the granule area variable, swelling capacity was high-throughput characterized, which allows for the whole evaluation to be completed within a couple of minutes. The proposed methodology showed a high accuracy and potential as a novel technique for characterizing gelatinization. Keywords: Gelatinization | Computer vision | Quantification | Canny detection | Mathematical morphology |
مقاله انگلیسی |
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A possibilistic mathematical programming model to control the flow of relief commodities in humanitarian supply chains
یک مدل برنامه ریزی ریاضی احتمالی برای کنترل جریان کالاهای امدادی در زنجیره های تأمین بشردوستانه-2021 In emergency situations, disaster relief organizations are faced with the difficult decision of how to allocate scarce resources in an efficient manner in order to provide the best possible relief action. This paper aims to provide an analytical model that will help relief organizations in reducing human suffering following a disaster while maintaining an acceptable level of cost efficiency. A mathematical model is introduced to optimize the relief distribution problem which considers the social cost —the total sum of logistics and deprivation costs. The fuzzy nature of the deprivation cost function is addressed with possibilistic mixed integer programming with fuzzy objectives to reflect variation in deprivation costs perceptions. The model is solved using the Rolling Horizon method in a sequence of iterations. In each iteration, part of the planning horizon is modeled in detail and the rest of the time horizon is represented in an aggregated manner. The model is tested both empirically and on a case study of internal displacement in northwest Syria. Computational results showed that considering the demographic structure in affected areas and reflecting it to the deprivation cost function helped to reach better prioritization in distribution of commodities. The rolling horizon methodology is also found to be efficient in solving large scale instances and in capturing the dynamic changes in demand and supply parameters. Keywords: Humanitarian logistics | Possibilistic linear programming | Rolling horizon | Deprivation cost | Inventory allocation |
مقاله انگلیسی |