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The book provides detailed descriptions, including more than 550 mathematical formulas, for more than 150 trading strategies across a host of asset classes and trading styles. These include stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility, real estate, distressed assets, cash, cryptocurrencies, weather, energy, inflation, global macro, infrastructure, and tax arbitrage. Some strategies are based on machine learning algorithms such as artificial neural networks, Bayes, and k-nearest neighbors. The book also includes source code for illustrating out-of-sample backtesting, around 2,000 bibliographic references, and more than 900 glossary, acronym and math definitions. The presentation is intended to be descriptive and pedagogical and of particular interest to finance practitioners, traders, researchers, academics, and business school and finance program students.
Building accurate algorithms for the optimization of picking orders is a difficult task, especially when one considers the delays of real-world situations. In warehouse environments, diverse algorithms must be developed to enhance the global performance relating to combining customer orders into picking orders to reduce wait times. The Handbook of Research on Metaheuristics for Order Picking Optimization in Warehouses to Smart Cities is a pivotal reference source that addresses strategies for developing able algorithms in order to build better picking orders and the impact of these strategies on the picking systems in which diverse algorithms are implemented. While highlighting topics such ABC optimization, environmental intelligence, and order batching, this publication examines common picking aspects in warehouse environments ranging from manual order picking systems to automated retrieval systems. This book is intended for researchers, teachers, engineers, managers, and practitioners seeking research on algorithms to enhance the order picking performance.
"This book is an insightful, well-balanced, stimulating SCM Strategy book that clearly tells managers, consultants, as well as educators that the SCM concept is not a fad but a must strategy to gain competitive advantage in today′s dynamic global market place. There are three major strengths. First, it is an unprecedented interdisciplinary SCM strategy book that explains how companies obtain, maintain, and even enhance competitive advantages based upon a well-laid SCM strategy. Second, it provides readers a unique, well-balanced framework for SCM strategy formulation. Third, it is a valuable contribution in the area of SCM in that it does a good job in explaining such a complicated SCM strategy to readers in such a simple manner." —Soonhong (Hong) Min, University of Oklahoma Author of the bestselling text Supply Chain Management, John T. Mentzer′s companion book Fundamentals of Supply Chain Management: Twelve Drivers of Competitive Advantage has been developed as a supplemental text for any course dealing with strategy and supply chains. Written in an entertaining, accessible style, Mentzer identifies twelve drivers of competitive advantage as clear strategic points managers can use in their companies. Research from more than 400 books, articles, and papers, as well as interviews with over fifty executives in major global companies, inform these twelve drivers. The roles of all of the traditional business functions—marketing, sales, logistics, information systems, finance, customer services, and management—in supply chain management are also addressed. Complete with cases and real-world examples from corporations around the world, the book′s exemplars will help students and practicing managers to more effectively understand, implement, and manage supply chains successfully.
This book addresses two significant research areas in an interdependent fashion. It is first of all a comprehensive but concise text that covers the recently developed and widely applicable methods of qualitative choice analysis, illustrating the general theory through simulation models of automobile demand and use. It is also a detailed study of automobile demand and use, presenting forecasts based on these powerful new techniques. The book develops the general principles that underlie qualitative choice models that are now being applied in numerous fields in addition to transportation, such as housing, labor, energy, communications, and criminology. The general form, derivation, and estimation of qualitative choice models are explained, and the major models - logit, probit, and GEV - are discussed in detail. And continuous/discrete models are introduced. In these, qualitative choice methods and standard regression techniques are combined to analyze situations that neither alone can accurately forecast. Summarizing previous research on auto demand, the book shows how qualitative choice methods can be used by applying them to specific auto-related decisions as the aggregate of individuals' choices. The simulation model that is constructed is a significant improvement over older models, and should prove more useful to agencies and organizations requiring accurate forecasting of auto demand and use for planning and policy development. The book concludes with an actual case study based on a model designed for the investigations of the California Energy Commission. Kenneth Train is Visiting Associate Professor in Economics at the University of California, Berkeley, and Director of Economic Research at Cambridge Systematics, Inc., also in Berkeley. Qualitative Choice Analysisis included in The MIT Press Transportation Studies Series, edited by Marvin L. Manheim.
The world of logistics has considerably changed due to globalization, modern information technology, and especially increasing ecological awareness. Large Supply Chain Management (SCM) systems are developing to global logistic networks. This book reflects major trends of the recent decade in SCM and, additionally, presents ideas and visions for logistic networks of the 21st century. Among the various aspects of SCM, emphasis is placed on reverse logistics: closing the loop of a supply chain by integrating waste materials into logistic management decisions.
This volume contains a selection of the best papers presented at the 8th International Conference on Industrial Engineering and Industrial Management, XX International Conference on Industrial Engineering and Operations Management, and International IIE Conference 2014, hosted by ADINGOR, ABEPRO and the IIE, whose mission is to promote links between researchers and practitioners from different branches, to enhance an interdisciplinary perspective of industrial engineering and management. The conference topics covered: operations research, modelling and simulation, computer and information systems, operations research, scheduling and sequencing, logistics, production and information systems, supply chain and logistics, transportation, lean management, production planning and control, production system design, reliability and maintenance, quality management, sustainability and eco-efficiency, marketing and consumer behavior, business administration and strategic management, economic and financial management, technological and organizational innovation, strategy and entrepreneurship, economics engineering, enterprise engineering, global operations and cultural factors, operations strategy and performance, management social responsibility, environment and sustainability. This book will be of interest to researchers and practitioners working in any of the fields mentioned above.
This book presents new insights and successful solutions to the operational problems of automated container terminals and cargo systems. It comprises reports on the state of the art, applications of quantitative methods, as well as case studies and simulation results. Its contributions are written by leading experts from academia and business and address practitioners and researchers in logistics, transportation, and management.
Optimal Regulation addresses the central issue of regulatory economics - how toregulate firms in a way that induces them to produce and price "optimally." It synthesizes the majorfindings of an extensive theoretical literature on what constitutes optimality in various situationsand which regulatory mechanisms can be used to achieve it. It is the first text to provide aunified, modern, and nontechnical treatment of the field.The book includes models for regulatingoptimal output, tariffs, and surplus subsidy schemes, and presents all of the material graphically,with clear explanations of often highly technical topics.Kenneth E. Train is Associate AdjunctProfessor in the Department of Economics and Graduate School of Public Policy at the University ofCalifornia, Berkeley. He is also Principal of the firm Cambridge Systematics.Topics include: Thecost structure of natural monopoly (economies of scale and scope). Characterization of firstandsecond-best optimality. Surplus subsidy schemes for attaining first-best optimality. Ramsey pricesand the Vogelsang-Finsinger mechanism for attaining them. Time-ofuse (TOU) prices and Riordan'smechanisms for attaining the optimal TOU prices' Multipart and self-selecting tariffs, and Sibley'smethod for using self-selecting tariffs to achieve optimality. The Averch-Johnson model of howrate-of-return regulation induces inefficiencies. Analysis of regulation based on the firm's returnon Output, costs, or sales. Price-cap regulation. Regulatory treatment of uncertainty and its impacton the firm's behavior. Methods of attaining optimality without direct regulation (contestability,auctioning the monopoly franchise.)