Academic literature on the topic 'Cash management problem with uncertain demands'

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Journal articles on the topic "Cash management problem with uncertain demands"

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Schroeder, Pascal, and Imed Kacem. "Competitive difference analysis of the cash management problem with uncertain demands." European Journal of Operational Research 283, no. 3 (2020): 1183–92. http://dx.doi.org/10.1016/j.ejor.2019.11.065.

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Song, Na, Wai-Ki Ching, Tak-Kuen Siu, and Cedric Ka-Fai Yiu. "On Optimal Cash Management under a Stochastic Volatility Model." East Asian Journal on Applied Mathematics 3, no. 2 (2013): 81–92. http://dx.doi.org/10.4208/eajam.070313.220413a.

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AbstractWe discuss a mathematical model for optimal cash management. A firm wishes to manage cash to meet demands for daily operations, and to maximize terminal wealth via bank deposits and stock investments that pay dividends and have uncertain capital gains. A Stochastic Volatility (SV) model is adopted for the capital gains rate of a stock, providing a more realistic way to describe its price dynamics. The cash management problem is formulated as a stochastic optimal control problem, and solved numerically using dynamic programming. We analyze the implications of the heteroscedasticity desc
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Pandey, Peeyush, Patel Jinil Ashvinbhai, Yushmita Singh, et al. "Modi Mangoes: managing an uncertain future." Emerald Emerging Markets Case Studies 12, no. 4 (2022): 1–18. http://dx.doi.org/10.1108/eemcs-06-2022-0208.

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Learning outcomes The case primarily focused on a real-life problem and shows that existing operations management tools can be used to solve a complex problem. Through this case, the participants will learn the application of the factor loading method and aggregate planning. Case overview/synopsis This case revolves around the Modi Agro Pvt. Ltd, a mango procurement and distribution business established in 1994 by Mr Dhanush Modi in Mumbai, India. Mr Mahendra Modi, son of the company owner, observed that the different seasons of cultivation and varied customer demands lead to changing workforc
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Lima, Relvas, Barbosa-Póvoa, and Morales. "Adjustable Robust Optimization for Planning Logistics Operations in Downstream Oil Networks." Processes 7, no. 8 (2019): 507. http://dx.doi.org/10.3390/pr7080507.

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The oil industry operates in a very uncertain marketplace, where uncertain conditions can engender oil production fluctuations, order cancellation, transportation delays, etc. Uncertainty may arise from several sources and inexorably affect its management by interfering in the associated decision-making, increasing costs and decreasing margins. In this context, companies often must make fast and precise decisions based on inaccurate information about their operations. The development of mathematical programming techniques in order to manage oil networks under uncertainty is thus a very relevan
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Rouzpeykar, Yaser, Roya Soltani, and Mohammad Ali Afashr Kazemi. "EFP-GA: An Extended Fuzzy Programming Model and a Genetic Algorithm for Management of the Integrated Hub Location and Revenue Model under Uncertainty." Complexity 2022 (July 6, 2022): 1–12. http://dx.doi.org/10.1155/2022/7801188.

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The aviation industry is one of the most widely used applications in transportation. Due to the limited capacity of aircraft, revenue management in this industry is of high significance. On the other hand, the hub location problem has been considered to facilitate the demands assignment to hubs. This paper presents an integrated p-hub location and revenue management problem under uncertain demand to maximize net revenue and minimize total cost, including hub establishment and transportation costs. A fuzzy programming model and a genetic algorithm are developed to solve the proposed model with
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Nasiri. "COORDINATED LOCATION, DISTRIBUTION AND INVENTORY DECISIONS IN SUPPLY CHAIN NETWORK DESIGN: A MULTI-OBJECTIVE APPROACH." South African Journal of Industrail Engineering 23, no. 2 (2012): 159–75. https://doi.org/10.7166/23-2-338.

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This research presents an integrated multi-objective distribution model for use in simultaneous strategic and operational food supply chain (SC) planning. The proposed method is adopted to allow use of a performance measurement system that includes conflicting objectives such as distribution costs, customer service level (safety stock holding), resource utilisation, and the total delivery time, with reference to multiple warehouse capacities and uncertain forecast demands. To deal with these objectives and enable the decision makers (DMs) to evaluate a greater number of alternative solutions,
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Martínez-Reyes, Andrés, Carlos L. Quintero-Araújo, and Elyn L. Solano-Charris. "Supplying Personal Protective Equipment to Intensive Care Units during the COVID-19 Outbreak in Colombia. A Simheuristic Approach Based on the Location-Routing Problem." Sustainability 13, no. 14 (2021): 7822. http://dx.doi.org/10.3390/su13147822.

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The coronavirus disease 2019, known as COVID-19, has generated an imminent necessity for personal protective equipment (PPE) that became essential for all populations and much more for health centers, clinics, hospitals, and intensive care units (ICUs). Considering this fact, one of the main issues for cities’ governments is the distribution of PPE to ICUs to ensure the protection of medical personnel and, therefore, the sustainability of the health system. Aware of this challenge, in this paper, we propose a simheuristic approach for supplying personal protective equipment to intensive care u
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Rahdar, Mohammad, Lizhi Wang, Jing Dong, and Guiping Hu. "Resilient Transportation Network Design under Uncertain Link Capacity Using a Trilevel Optimization Model." Journal of Advanced Transportation 2022 (January 20, 2022): 1–16. http://dx.doi.org/10.1155/2022/5023518.

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This study addresses uncertainty in a transportation network by proposing a trilevel optimization model, which improves resiliency against uncertain disruptions. The goal is to minimize the total travel time by designing a resilient transportation network under uncertain disruptions and deterministic origin-destination demands. The trilevel optimization model has three levels. The lower level determines the network flow, and the middle level assesses the network’s resiliency by identifying the worst-case scenario disruptions that could lead to maximal travel time. The upper-level takes the sys
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Chen, Xin, and David Simchi-Levi. "A NEW APPROACH FOR THE STOCHASTIC CASH BALANCE PROBLEM WITH FIXED COSTS." Probability in the Engineering and Informational Sciences 23, no. 4 (2009): 545–62. http://dx.doi.org/10.1017/s0269964809000242.

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The stochastic cash balance problem is a periodic review inventory problem faced by a firm in which the customer demands might be positive or negative. At the beginning of each time period, the firm may decide to replenish the inventory or return excess stock. Both the ordering cost and the return cost include a fixed component and a variable component. A holding or penalty cost is charged depending on whether the inventory level is positive or negative. The objective of the firm is to find an ordering and return policy so as to minimize the total expected cost over the entire planning horizon
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Mejia, Jose, Liliana Avelar-Sosa, Boris Mederos, and Jorge L. García-Alcaraz. "Inventory Model with Stochastic Demand Using Single-Period Inventory Model and Gaussian Process." Processes 10, no. 4 (2022): 783. http://dx.doi.org/10.3390/pr10040783.

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Proper inventory management is vital to achieving sustainability within a supply chain and is also related to a company’s cash flow through the funds represented by the inventory. Therefore, it is necessary to balance excess inventory and insufficient inventory. However, this can be difficult to achieve in the presence of stochastic demand because decisions must be made in an uncertain environment and the inventory policy bears risks associated with each decision. This study reports an extension of the single-period model for the inventory problem under uncertain demand. We proposed incorporat
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Dissertations / Theses on the topic "Cash management problem with uncertain demands"

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Schroeder, Pascal. "Performance guaranteeing algorithms for solving online decision problems in financial systems." Electronic Thesis or Diss., Université de Lorraine, 2019. http://www.theses.fr/2019LORR0143.

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Cette thèse contient quelques problèmes de décision financière en ligne et des solutions. Les problèmes sont formulés comme des problèmes en ligne (OP) et des algorithmes en ligne (OA) sont créés pour résoudre. Comme il peut y avoir plusieurs OAs pour le même OP, il doit y avoir un critère afin de pouvoir faire des indications au sujet de la qualité d’un OA. Dans cette thèse ces critères sont le ratio compétitif (c), la différence compétitive (cd) et la performance numérique. Un OA qui a un c ou cd plus bas qu’un autre est à préférer. Un OA qui possède le c le plus petit est appelé optimal. No
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Bernardo, Papini Marcella Verfasser], Pannek [Akademischer Betreuer] Pannek, Pannek [Gutachter] Pannek, and Hans-Dietrich [Gutachter] [Haasis. "Robust Capacitated Vehicle Routing Problem with Uncertain Demands / Marcella Bernardo Papini ; Gutachter: Pannek Pannek, Hans-Dietrich Haasis ; Betreuer: Pannek Pannek." Bremen : Staats- und Universitätsbibliothek Bremen, 2019. http://d-nb.info/1196286310/34.

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Book chapters on the topic "Cash management problem with uncertain demands"

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Werners, Brigitte, and Yuriy Kondratenko. "Alternative Fuzzy Approaches for Efficiently Solving the Capacitated Vehicle Routing Problem in Conditions of Uncertain Demands." In Complex Systems: Solutions and Challenges in Economics, Management and Engineering. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69989-9_31.

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Boscoianu, Mircea, Costel Ceocea, and Aurel Mihail Țîțu. "Adapting Strategies of Portfolio Management to VUCA Environments: The Case of Romania." In Contributions to Management Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-60343-3_11.

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AbstractThe recent multiple crises of the 2020–2023 imposed the integration of the concept of VUCA environments (volatility–uncertainty–complexity–ambiguity) at the level of the capital markets, as an indisputable reality. These processes have, in fact, led to major changes in the perception of the markets impacting the understanding of new problems, respectively, the action of the managers and the implementation of the portfolio management strategies. Managing portfolios in VUCA environments involves reconsidering portfolio management objectives that must be better adapted to investors’ requi
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Nasiri, Gholam Reza, and Fariborz Jolai. "Supply Chain Network Design in Uncertain Environment." In Optimization Techniques for Problem Solving in Uncertainty. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5091-4.ch010.

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Dynamic environment imposes such conditions that make it necessary for companies to consider sources of uncertainty in designing core business processes and optimizing supply chain operations. Efficient management of a supply system requires an integrated approach towards various operational functions and related source of uncertainties. Uncertain conditions in supply network design problem such as market demands, delivery time, and facility capacity are considered and incorporated by many studies at the mathematical programming formulations as well. In this chapter, extensive review of existi
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Zurbriggen, Cristina, and Mariana González Lago. "Navigating the Future through Experimental Policy Design." In The Future of Public Administration - Adapting to a Dynamic World [Working Title]. IntechOpen, 2024. http://dx.doi.org/10.5772/intechopen.1004169.

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Innovative strategies in public policy design are crucial to effectively address the complex and interconnected environmental challenges governments face today. The intricate and uncertain nature of these problems often requires experimental coproduction solutions that integrate and synthesize diverse areas of expertise and stakeholder viewpoints and demand experimental and adaptive capacity to respond in turbulent times. As policy-generative experiments in policy design spread and gain legitimacy, they pose substantial challenges: What challenges do governments encounter in implementing exper
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Polat, Olcay. "Designing of Container Feeder Service Networks Under Unstable Demand Conditions." In Logistics and Supply Chain Management in the Globalized Business Era. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-8709-6.ch006.

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The COVID-19 pandemic has greatly magnified supply challenges in all industries, and virus waves continue to cause an extraordinary amount of variation in both the demand for and the availability of necessary products. This uncertainty has also forced many organizations including container liner shipping to redesign their supply chain. Feeder services from hub ports are essential chain of shipping networks. This chapter addresses the design of feeder networks under consideration of demand fluctuations over the year. For this purpose, a perturbation-based variable neighbourhood search approach
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Rajesh, R., S. Pugazhendhi, and K. Ganesh. "Genetic Algorithm and Particle Swarm Optimization for Solving Balanced Allocation Problem of Third Party Logistics Providers." In Management Innovations for Intelligent Supply Chains. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2461-0.ch010.

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Third party logistics (3PL) service providers play a growing responsibility in the management of supply chain. The global and competitive business environment of 3PLs has recognized the significance of a speedy and proficient service towards the customers in the past few decades. Particularly in warehousing, distribution, and transportation services, a number of customers anticipate 3PLs to improve lead times, fill rates, inventory levels, etc. Therefore, the 3PLs are under demands to convene a range of service necessities of customers in an active and uncertain business environment. As a cons
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Farmani, R., D. A. Savic, H. J. Henriksen, J. L. Molina, R. Giordano, and J. Bromley. "Evolutionary Bayesian Belief Networks for Participatory Water Resources Management under Uncertainty." In Green Technologies. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-60960-472-1.ch309.

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A participatory integrated (social, economic, environmental) approach based on causal loop diagram, Bayesian belief networks and evolutionary multiobjective optimisation is proposed for efficient water resources management. The proposed methodology incorporates all the conflicting objectives in the decision making process. Causal loop diagram allows a range of different factors to be considered simultaneously and provides a framework within which the contributions of stakeholders can be taken into account. Bayesian belief networks takes into account uncertainty by assigning probability to thos
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Nene, Dr Sanele Enock. "ARTIFICIAL INTELLIGENCE FOR SUSTAINABILITY: INNOVATIONS IN BUSINESS AND FINANCIAL SERVICES." In Artificial Intelligence and Emerging Technologies. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/nbennurch302.

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Artificial Intelligence (AI) is transforming how we live and projecting how future should look like. AI is a form of technology developed to mimic human intelligence through decision making, problem solving, learning and improving abilities to meet the demands posited by the environment. The businesses must be agile enough to effectively respond to the markets that are volatile, uncertain, complex and ambiguous. As a result, AI is a critical tool that businesses should adopt to respond to these markets and to remain sustainable. Global agents such as United Nations must ensure that developing
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Conference papers on the topic "Cash management problem with uncertain demands"

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Rezapour, Shabnam, Janet K. Allen, and Farrokh Mistree. "Uncertainty Propagation in a Supply Chain / Network With Uncertain Facility Performance." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34255.

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Decentralized production systems in supply chains / networks makes them more profitable and agile than traditional enterprises with centralized production systems. However, this decentralization makes supply chains / networks more vulnerable respect to uncertainties which are unavoidable. Today’s supply chains / networks producing and supplying their products to markets are characterized by uncertain demands (called demand-side uncertainty) and uncertainties associated with the performances of their constituent production facilities (called supply-side uncertainty). Supply-side uncertainty is
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De Filippo, Allegra, Michele Lombardi, and Michela Milano. "Methods for off-line/on-line optimization under uncertainty." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/177.

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In this work we present two general techniques to deal with multi-stage optimization problems under uncertainty, featuring off-line and on-line decisions. The methods are applicable when: 1) the uncertainty is exogenous; 2) there exists a heuristic for the on-line phase that can be modeled as a parametric convex optimization problem. The first technique replaces the on-line heuristics with an anticipatory solver, obtained through a systematic procedure. The second technique consists in making the off-line solver aware of the on-line heuristic, and capable of controlling its parameters so as to
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De Filippo, Allegra, Michele Lombardi, and Michela Milano. "How to Tame Your Anticipatory Algorithm." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/150.

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Sampling-based anticipatory algorithms can be very effective at solving online optimization problems under uncertainty, but their computational cost may be prohibitive in some cases. Given an arbitrary anticipatory algorithm, we present three methods that allow to retain its solution quality at a fraction of the online computational cost, via a substantial degree of offline preparation. Our approaches are obtained by combining: 1) a simple technique to identify likely future outcomes based on past observations; 2) the (expensive) offline computation of a "contingency table"; and 3) an efficien
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Jaržemskis, Andrius, and Ilona Jaržemskienė. "FORECAST METHODS FOR INVESTMENT OF COUNTRY WIDE ELECTRIC VEHICLE CHARGING STATIONS: LITHUANIAN CASE." In 12th International Scientific Conference „Business and Management 2022“. Vilnius Gediminas Technical University, 2022. http://dx.doi.org/10.3846/bm.2022.753.

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The aim of this article is to present a complex model for forecasting the required investments based on the forecast of the increase in the number of electric vehicles and their demand for energy and investments. Scientific problem is that current approach on forecasting of electric vehicles is to abstract, forecast models can’t be transferred from country to country. This article proposes a model of forecasting investments based on the fore-cast of the increase in the number of electric vehicles and their demand on energy. The findings of the Lithuanian case analysis, which is expressed in th
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Ayağ, Zeki. "A COMPARISON STUDY OF FUZZY AHP-BASED MCDM METHODS ON GREEN CONCEPT SELECTION PROBLEM." In MBP 2025 London International Conference on Management Business Practices, 22-23 April. Global Research & Development Services Publishing, 2025. https://doi.org/10.20319/icssh.2025.113114.

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The demand for green products has dramatically increased because the importance and public awareness of the preservation of natural environment was taken into consideration much more last two decades. As a result of this, manufacturing companies especially have been forced to design more green products, resulting in a problem of how they incorporate environmental issues into their design and evaluate concept options. The need for practical decision-making tools to address this problem is rapidly evolving since the problem turns into a multiple-criteria decision making (MCDM) problem in the pre
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Dong, Hang, Boshi Wang, Bo Qiao, et al. "Predictive Job Scheduling under Uncertain Constraints in Cloud Computing." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/499.

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Capacity management has always been a great challenge for cloud platforms due to massive, heterogeneous on-demand instances running at different times. To better plan the capacity for the whole platform, a class of cloud computing instances have been released to collect computing demands beforehand. To use such instances, users are allowed to submit jobs to run for a pre-specified uninterrupted duration in a flexible range of time in the future with a discount compared to the normal on-demand instances. Proactively scheduling those pre-collected job requests considering the capacity status ove
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Deppen, Timothy O., Andrew G. Alleyne, Kim A. Stelson, and Jonathan J. Meyer. "Model Predictive Control of an Electro-Hydraulic Powertrain With Energy Storage." In ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control. ASMEDC, 2011. http://dx.doi.org/10.1115/dscc2011-5969.

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This paper presents a model predictive control approach to solving the energy management problem within a series hydraulic hybrid powertrain. The hydraulic hybrid utilizes a high pressure accumulator for energy storage which has superior power density than conventional battery technology. This makes fluid power attractive for urban driving applications in which there are frequent starts and stops and large startup power demands. Model predictive control was chosen for control design because this technique requires no information about the future drive cycle, which can be highly uncertain in ur
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Ghedan, Shawket, Meher Surendra, Agustin Maqui, et al. "Rapid and Efficient Waterflood Optimization Using Augmented AI Approach in a Complex Offshore Field." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/207458-ms.

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Abstract Waterfloods are amongst the most widely implemented methods for oil field development. Despite their vast implementation, operational bottlenecks such as lack of surveillance and optimization tools to guide fast paced decisions render most of these sub-optimal. This paper presents a novel machine-learning, reduced-physics approach to optimize an exceptionally complex off-shore waterflood in the Gulf of Suez. Leveraging a hybrid data-driven and physics approach, the water flooding scheme in Nezzezat reservoir was optimized to improve reservoir voidage replacement, increase oil producti
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Reports on the topic "Cash management problem with uncertain demands"

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Mayfield, Colin. Capacity Development in the Water Sector: the case of Massive Open On-line Courses. United Nations University Institute for Water, Environment and Health, 2017. http://dx.doi.org/10.53328/mwud6984.

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The Sustainable Development Goal 6 targets are all dependent on capacity development as outlined in SDG 6a “Expand international cooperation and capacity-building support to developing countries in water- and sanitation related activities and programmes “. Massive Open On-line Courses (MOOCs) and distance learning in general have a significant role to play in this expansion. This report examines the role that MOOCs and similar courses could play in capacity development in the water sector. The appearance of MOOCs in 2010/11 led within 4 years to a huge increase in this type of course and in st
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Ocampo-Gaviria, José Antonio, Roberto Steiner Sampedro, Mauricio Villamizar Villegas, et al. Report of the Board of Directors to the Congress of Colombia - March 2023. Banco de la República de Colombia, 2023. http://dx.doi.org/10.32468/inf-jun-dir-con-rep-eng.03-2023.

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Banco de la República is celebrating its 100th anniversary in 2023. This is a very significant anniversary and one that provides an opportunity to highlight the contribution the Bank has made to the country’s development. Its track record as guarantor of monetary stability has established it as the one independent state institution that generates the greatest confidence among Colombians due to its transparency, management capabilities, and effective compliance with the central banking and cultural responsibilities entrusted to it by the Constitution and the Law. On a date as important as this,
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