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Author: Zhanyue Wang
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
In this paper, we consider a class of inventory management applications where the distribution of the underlying demand is unknown and the manager must make an inventory-ordering decision in each period based only on the past demand data. The standard performance measure is regret, which is the cost difference between a learning algorithm and the clairvoyant (full-information) benchmark. When the benchmark is chosen to be the (full-information) optimal policy, we propose a new nonparametric learning algorithm that combines the Sample Average Approximation (SAA) approach and the Stochastic Gradient Descent (SGD) method to admit a regret bound of $ mathcal{O}( sqrt{K})$ ($K$ is the planning horizon), which matches the theoretical lower bound. We demonstrate the usefulness of the algorithm by applying it to two classic inventory problems: dual-sourcing and two-echelon inventory problems, under the assumption that the manager does not know the demand distributions and has access only to historical data. We also conduct numerical experiments to demonstrate the effectiveness of our proposed algorithms.
Author: Zhanyue Wang
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
In this paper, we consider a class of inventory management applications where the distribution of the underlying demand is unknown and the manager must make an inventory-ordering decision in each period based only on the past demand data. The standard performance measure is regret, which is the cost difference between a learning algorithm and the clairvoyant (full-information) benchmark. When the benchmark is chosen to be the (full-information) optimal policy, we propose a new nonparametric learning algorithm that combines the Sample Average Approximation (SAA) approach and the Stochastic Gradient Descent (SGD) method to admit a regret bound of $ mathcal{O}( sqrt{K})$ ($K$ is the planning horizon), which matches the theoretical lower bound. We demonstrate the usefulness of the algorithm by applying it to two classic inventory problems: dual-sourcing and two-echelon inventory problems, under the assumption that the manager does not know the demand distributions and has access only to historical data. We also conduct numerical experiments to demonstrate the effectiveness of our proposed algorithms.
Author: Christian L. Dunis
Publisher: Springer
ISBN: 1137488808
Category : Business & Economics
Languages : en
Pages : 349
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Book Description
As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.
Author: Tamás Varga
Publisher: Elsevier Inc. Chapters
ISBN: 0128069058
Category : Computers
Languages : en
Pages : 29
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Book Description
Advanced inventory management in complex supply chains requires effective and robust nonlinear optimization due to the stochastic nature of supply and demand variations. Application of estimated gradients can boost up the convergence of Particle Swarm Optimization (PSO) algorithm but classical gradient calculation cannot be applied to stochastic and uncertain systems. In these situations Monte-Carlo (MC) simulation can be applied to determine the gradient. We developed a memory-based algorithm where instead of generating and evaluating new simulated samples the stored and shared former function evaluations of the particles are sampled to estimate the gradients by local weighted least squares regression. The performance of the resulted regional gradient-based PSO is verified by several benchmark problems and in a complex application example where optimal reorder points of a supply chain are determined.
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1466624566
Category : Computers
Languages : en
Pages : 2335
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Book Description
Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way. Data Mining: Concepts, Methodologies, Tools, and Applications is a comprehensive collection of research on the latest advancements and developments of data mining and how it fits into the current technological world.
Author: Per A. Holst
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 472
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Book Description
Author: Koyuncugil, Ali Serhan
Publisher: IGI Global
ISBN: 1616928670
Category : Computers
Languages : en
Pages : 356
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Book Description
Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection has never been more important, as the research this book presents an alternative to conventional surveillance and risk assessment. This book is a multidisciplinary excursion comprised of data mining, early warning systems, information technologies and risk management and explores the intersection of these components in problematic domains. It offers the ability to apply the most modern techniques to age old problems allowing for increased effectiveness in the response to future, eminent, and present risk.
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 1460
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Book Description
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Author: Yves Lechevallier
Publisher: Springer Science & Business Media
ISBN: 3790826049
Category : Computers
Languages : en
Pages : 627
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Book Description
Proceedings of the 19th international symposium on computational statistics, held in Paris august 22-27, 2010.Together with 3 keynote talks, there were 14 invited sessions and more than 100 peer-reviewed contributed communications.
Author: Mamoun Alazab
Publisher: Springer
ISBN: 3030130576
Category : Computers
Languages : en
Pages : 246
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Book Description
Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points.
Author:
Publisher:
ISBN:
Category : Automatic control
Languages : en
Pages :
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Book Description
