با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
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Accounting as a technology of neoliberalism: The accountability role of IPSAS in Nigeria
حسابداری به عنوان فناوری نئولیبرالیسم: نقش پاسخگویی IPSAS در نیجریه-2021 This paper critically examines the implications for Nigeria’s indebtedness of neoliberalism
as a neo-colonial dependency concept and International Public Sector Accounting
Standards (IPSAS) as a technology of a new form of economic imperialism. As Nigeria’s
huge oil and gas revenues continue to be lost to corruption, the country relies on loans
from Paris Club countries and International Financial Institutions (IFIs), notably the
World Bank. In 1999, when the country changed from military to democratic
governance, Nigeria’s debt to the Paris Club and the World Bank was $30bn. With
pressure from the Paris Club and the World Bank to repay its debts, the new democratic
Nigerian government sought debt forgiveness and rescheduling. Although the World
Bank, representing the creditors in debt negotiation, does not go into specific accounting
standards to be adopted by debtor nations, the Bank does require Nigeria to embrace
neoliberal economic reforms (including public sector reporting framework that produces
consistently relevant and reliable financial information – which denotes IPSAS). Despite
the partial debt forgiveness, repayment of the balance of the debt and adoption of IPSAS,
Nigeria remains endemically corrupt, relies on loans from powerful nations and IFIs, and
has again become debt-laden. Contrary to neoliberal assumptions therefore, we provide
the evidence that better accounting may not necessarily be a panacea for economic
development.
keywords: نئولیبرالیسم | موسسات مالی بین المللی (IFIS) | حسابداری بین المللی بخش دولتی | استانداردها (خود) | فساد | شفافیت و پاسخگویی | Neoliberalism | International Financial Institutions (IFIs) | International Public Sector Accounting | Standards (IPSAS) | Corruption | Transparency and Accountability |
مقاله انگلیسی |
12 |
Three-scale integrated optimization model of furnace simulation, cyclic scheduling, and supply chain of ethylene plants
سه سطح مقیاس مدل بهینه سازی شبیه سازی کوره ، برنامه ریزی چرخه ای ، و زنجیره تامین کارخانه های اتیلن-2021 In order to explore the potential of profit margin improvement, a novel three-scale integrated optimization model of furnace simulation, cyclic scheduling, and supply chain of ethylene plants is proposed and evaluated. A decoupling strategy is proposed for the solution of the three-scale model, which uses our previously proposed reactor scale model for operation optimization and then transfers the obtained results as a parameter table in the joint MILP optimization of plant-supply chain scale for cyclic scheduling. This optimization framework simplifies the fundamental MINLP into several sub-models, and improves the interpretability and extendibility. In the evaluation of an industrial case, a profit increase at a percentage of 3.25% is attained in optimization compared to the practical operations. Further sensitivity analysis is carried out for strategy evolving study when price policy, supply chain, and production requirement parameters are varied. These results could provide useful suggestions for petrochemical enterprises on thermal cracking production. Keywords: three-scale integrated optimization | cyclic scheduling | supply chain | MILP | thermal cracking |
مقاله انگلیسی |
13 |
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 |
14 |
Flowshop scheduling with sequence dependent setup times and batch delivery in supply chain
برنامه ریزی Flowshop با زمان تنظیمات وابسته به توالی و تحویل دسته ای در زنجیره تامین-2021 With the emergence of advanced manufacturing and Industry 4.0 technologies, there is a growing interest in coordinating the production and distribution in supply chain management. This paper addresses the production and distribution problems with sequence dependent setup time for multiple customers in flow shop environments. In this complex decision-making problem, an efficient scheduling approach is required to optimize the trade-off between the total cost of tardiness and batch delivery. To achieve this, three new metaheuristic algorithms such as Differential Evolution with different mutation strategy variation and a Moth Flame Optimization, and Levy-Flight Moth Flame Optimization algorithm are proposed and presented. In addition, a design-of- experiment method is used to identify the best possible parameters for the proposed approaches for the problem under study. The proposed algorithms are validated on a set of problem instances. The variants of differential evolution performed better than the other compared algorithms and this demonstrates the effectiveness of the proposed approach. The algorithms are also validated using an industrial case study. Keywords: Flow shop scheduling | Supply chain | Differential evolution | Moth flame optimization |Levy-flight moth flame optimization |
مقاله انگلیسی |
15 |
An agent-based approach for project-driven supply chain problem under information asymmetry and decentralized decision-making
یک رویکرد مبتنی بر عامل برای مشکل زنجیره تأمین پروژه محور تحت عدم تقارن اطلاعات و تصمیم گیری غیرمتمرکز-2021 In a project-driven supply chain, the project schedule and material supply influence one another. The effective decision-making process between the project manager and the suppliers can promote the flexibility and competitiveness of supply chains. However, due to their incompatible objectives, the suppliers are reluctant to disclose private information. By incorporating information asymmetry, we build a model to describe the decentralized decision-making process. The project manager does not know the lead time and the production/ transportation cost of the material suppliers accurately. To build an effective alliance in the supply chain, different contracts are considered to provide a positive or negative incentive for the suppliers, including a non- financial incentive contract with continuous orders. Then, we present a framework that integrates the agent- based approach and evolutionary algorithm. In the framework, the agents not only negotiate with each other to complete a solution but also jointly evaluate the solutions generated by the evolutionary algorithm. Finally, an experiment is conducted to compare the agent-based approach and the classical NSGA-II under information symmetry. The results show that the gap between the algorithms is acceptable, especially for a large project. The results also show that the non-financial incentive contract is beneficial to all the players in the supply chain. Keywords: Project scheduling | Multi-agent system | Supply chain coordination | Contracting |
مقاله انگلیسی |
16 |
A multi-functional tri-objective mathematical model for the pharmaceutical supply chain considering congestion of drugs in factories
یک مدل ریاضی سه هدفه چند منظوره برای زنجیره تأمین دارویی با توجه به ازدحام داروها در کارخانه ها-2021 Supply Chain Management (SCM), by way of one of the critical issues in the managerial aspect, plays a significant role in tackling humanitarian problems and difficulties. Due to some limitations (e.g., production capacity and storage capacity) and desires (e.g., cost reduction and rising revenues), supply chain managers always seek the best response to the amount and type of communication between different SCM levels. In the upcoming research, a Pharmaceutical Supply Chain (PSC) with three objective functions is developed, aiming to simultaneously minimize total costs, unfulfilled demands, and reduce the waiting time at the factory entrance. In the forth- coming research, the subject literature and research in the PSC modeling and problem-solving are discussed. A nonlinear programming model is then proposed in line with the previous research to solve the existing short- comings. Also, multi-objective decision-making methods are used to match the conflicting objectives of the model simultaneously. Then, GAMS commercial software is used to solve the problem of different sizes. Finally, the wide sensitivity analysis and evaluation of the results are discussed, and future development suggestions are presented. Keywords: Pharmaceutical supply chain | Perishability | Scheduling | Inventory | Queuing theory |
مقاله انگلیسی |
17 |
پردازش فاضلاب لبنی و کنترل خودکار بازیافت زباله در تصفیه خانه فاضلاب شهری براساس بررسیهای مدلسازی
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 9 - تعداد صفحات فایل doc فارسی: 30 براساس مدل کالیبره شده برای یک تصفیهخانه فاضلاب شهری بی هوازی - آنوکسیک - هوازی (A2O) (WWTP)، این تحقیق راهحلهای عملی، تنظیمات سیستم کنترل و شرایط عملیاتی بهینه برای پردازش فاضلاب لبنی را بررسی و پیشنهاد کرد. مطالعه حالت پایدار در مورد افزودن مقادیر مختلف روزانه فاضلاب لبنی در خط آب WWTP نشان داد که با یافتن حداقل غلظت نیتروژن کل در پساب آب، موثرترین مقدار باید تصفیه شود. بررسیهای پویا در مورد افزودن مقادیر مختلف فاضلاب روزانه، انگیزههای پیکربندی سیستم کنترل آبشاری پیشنهادی را براساس کنترل غلظت آمونیاک یا نیترات در راکتورهای هوادهی شده، مرتبط با نیترات و کنترل غلظت نیتریت در رآکتور بیهوازی نشان داد. بهترین دورههای زمانی و طول مدت برای برنامه ریزی پردازش فاضلاب لبنی جستجو و یافت شد. نتایج اولیه انگیزههای توزیع اضافی فاضلاب لبنی را در طول ۲ ساعت، در بالاترین لحظات غلظت ورودی نشان داد. تحقیقات بیشتر، با تکیهبر روش بهینهسازی الگوریتم ژنتیک، نشان داد که برنامهریزی روزانه بهتر برای افزودن فاضلاب لبنی ممکن است به دست آید. در مقایسه با عملیات عادی، برنامه زمانبندی بهینه تصفیه فاضلاب لبنی بهبود شاخص عملکرد کلی ۱۳.۳۶ % را در زمانی که روزانه 1:52p.m بود، نشان داد. سپس با استفاده از روش بهینهسازی، زمان و طول مدت یک ساعت برنامه مورد استفاده قرار گرفت. نتایج انگیزههای دوگانه یا دوچندان بازیابی کربن و مواد مغذی، مرتبط با مزایای انرژی و کیفیت پساب در عملیات WWTP را نشان میدهد.
کلمات کلیدی: تصفیه فاضلاب | فاضلاب صنایع لبنی | مدلسازی | بازیابی کربن و مواد مغذی | برنامه زمانبندی بهینه |
مقاله ترجمه شده |
18 |
Integrated computer vision algorithms and drone scheduling
الگوریتم های یکپارچه بینایی ماشین و برنامه ریزی هواپیماهای بدون سرنشین-2021 Computer vision algorithms have attained significant accuracy in the
past decade, among which arguably the most important one is deep
neural networks. Unmanned aerial vehicles, commonly called drones,
equipped with cameras, offer a convenient, efficient, and cost-effective
way of collecting a large set of images. Combining drones and computer vision algorithms can automate the monitoring and surveying of
infrastructure systems, for example, car detection (Maria et al., 2016),
pedestrian and bicycle volume data collection (Kim, 2020), and road
degradation survey (Leonardi et al., 2018). However, the existing
research has been largely driven by two independent streams of expertise: computer vision and drone scheduling. Computer scientists strive to
design more accurate computer vision algorithms without much
consideration of how the images are collected, whereas operations researchers endeavor to design drone routing algorithms to collect a given
set of images in the most efficient manner. We suggest that the planning
of images to collect (number and locations of images, amongst others)
and the design of—more often than not, the choice of—computer vision
algorithms should be determined holistically instead of independently.
Section 2 presents an example to show the number of images to collect
depends on the accuracy of the computer vision algorithms. Section 3
lays out the roadmap for future research direction.
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مقاله انگلیسی |
19 |
Pharmaceutical R & D pipeline management under trial duration uncertainty
مدیریت خط لوله تحقیق و توسعه دارویی تحت عدم قطعیت آزمایش-2020 We consider a pharmaceutical Research & Development (R & D) pipeline management problem under two significant uncertainties: the outcomes of clinical trials and their durations. We present an Approximate Dynamic Programming (ADP) approach to solve the problem efficiently. Given an initial list of potential drug candidates, ADP derives a policy that suggests the trials to be performed at each decision point and state. For the classical R&D pipeline planning problem with deterministic trial durations, we compare our ADP approach with other methods from the literature, and find that it can find better solutions more quickly in particular for larger problem instances. For the case with stochastic trial durations, we compare the ADP algorithm with a myopic approach and show that the expected net profit obtained by the derived ADP policy is higher (almost 20% for a 10-drug portfolio). Keywords: Dynamic programming | Pharmaceutical R&D pipeline management | Heuristics | Approximate dynamic programming | Project scheduling |
مقاله انگلیسی |
20 |
Truck scheduling in a multi-door cross-docking center with partial unloading : Reinforcement learning-based simulated annealing approaches
زمانبندی کامیون در یک مرکز متصل متقابل چند درب با تخلیه جزئی: رویکردهای بازپخت شبیه سازی شده مبتنی بر یادگیری تقویتی -2020 In this paper, a truck scheduling problem at a cross-docking center is investigated where inbound trucks are also
used as outbound. Moreover, inbound trucks do not need to unload and reload the demand of allocated destination,
i.e. they can be partially unloaded. The problem is modeled as a mixed integer program to find the
optimal dock-door and destination assignments as well as the scheduling of trucks to minimize makespan. Due to
model complexity, a hybrid heuristic-simulated annealing is developed. A number of generic and tailor-made
neighborhood search structures are also developed to efficiently search solution space. Moreover, some reinforcement
learning methods are applied to intellectually learn more suitable neighborhood search structures in
different situations. Finally, the numerical study shows that partial unloading of compound trucks has a crucial
impact on makespan reduction. Keywords: Logistics | Cross docking | Truck scheduling | Simulated annealing | Reinforcement learning |
مقاله انگلیسی |