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Optimization in Industry: Volume 1, Optimization Techniques
by T.A.J. NicholsonAs optimization techniques have developed, a gap has arisen between the people devising the methods and the people who actually need to use them. Research into methods is necessarily long-term and located usually in academic establishments; whereas the application of an optimization technique, normally in an industrial environment, has to be justified financially in the short term. The gap is probably inevitable; but there is no need for textbooks to reflect it. Teaching of optimization techniques separately from their connection with applications is pointless. This book gives a detailed exposition of the techniques.In this first volume, T. A. J. Nicholson demonstrates the full range of techniques available to the practitioner for the solution of varying problems. For each technique, the background reasoning behind its development is explained in simple terms; where helpful it is supported by a geometrical argument; and the iterative algorithm for finding the optimum is defined clearly. These steps enable the reader not only to see plainly what is happening in the method but also to reach a level of understanding necessary to write computer programs for optimization techniques.Problems are tackled in the same way--by searching a feasible region for an optimum. This approach helps the reader to develop the most essential of all skills--selecting appropriate techniques for different circumstances. The numerous worked examples in the text, supported by worked solutions, and the exercises at the end of the chapters are important aids to learning and to teachers. This book serves as an introduction to optimization techniques for students as well as a reference work for the practitioner in business and industry.
Optimization in Large Scale Problems: Industry 4.0 and Society 5.0 Applications (Springer Optimization and Its Applications #152)
by Panos M. Pardalos Marzieh Khakifirooz Mahdi FathiThis volume provides resourceful thinking and insightful management solutions to the many challenges that decision makers face in their predictions, preparations, and implementations of the key elements that our societies and industries need to take as they move toward digitalization and smartness. The discussions within the book aim to uncover the sources of large-scale problems in socio-industrial dilemmas, and the theories that can support these challenges. How theories might also transition to real applications is another question that this book aims to uncover. In answer to the viewpoints expressed by several practitioners and academicians, this book aims to provide both a learning platform which spotlights open questions with related case studies. The relationship between Industry 4.0 and Society 5.0 provides the basis for the expert contributions in this book, highlighting the uses of analytical methods such as mathematical optimization, heuristic methods, decomposition methods, stochastic optimization, and more. The book will prove useful to researchers, students, and engineers in different domains who encounter large scale optimization problems and will encourage them to undertake research in this timely and practical field. The book splits into two parts. The first part covers a general perspective and challenges in a smart society and in industry. The second part covers several case studies and solutions from the operations research perspective for large scale challenges specific to various industry and society related phenomena.
Optimization in the Agri-Food Supply Chain: Recent Studies
by Diala Dhouib Mayssa Koubaa Mohamed Haykal Ammar Sirine MnejjaThis book discusses the optimization of supply chains in the agri-food and animal industries, and focuses on the integration of technology and sustainability practices. It explores the use of emerging technologies like IoT, Blockchain and AI in supply chain management, and also addresses the need for resilient supply chains and strategies for risk management. Optimization in the Agri-Food Supply Chain provides an overview of various studies conducted in the field, including topics such as the impact of climate change, sustainable initiatives, inventory management activities and the dynamics of specific supply chain systems. It also discusses the use of underutilized crops, optimization techniques, forecasting methods, circular production and the role of open innovation in the food supply chain. Overall, the book aims to contribute to the knowledge on supply chain optimization and also provide insights and recommendations for enhancing efficiency and sustainability in the agri-food and animal industries.
Optimization Issues in Web and Mobile Advertising
by Subodha KumarThis book provides a comprehensive overview of optimization issues and models in web and mobile advertising. It begins by discussing the evolution of web advertising over time. This is followed by the discussion of prominent pricing models. The reader is provided with a basic overview of different optimization issues involved in web advertising. The earlier models mainly considered the problem of scheduling ads competing to be placed on a web page. Here, the ads were specified by geometry and display frequency, and both of these factors were considered in developing a solution to the advertisement scheduling problem. These models were similar in nature to the problem of scheduling ads on newspaper or television, but the pricing structure in these models were different from those in newspaper or television ads. As the web advertising evolved, the initial models were augmented by considering how the schedule of ads is changed based on individual user click behavior. Thus, these models considered personalization in web advertising. The book also presents methods to help solve these models. More recently, there has been tremendous growth in mobile advertising. This book also provides the details of business model in mobile advertising, and presents solutions for the optimization problem involved in mobile advertising. Additionally this book looks to key future trends in web and mobile advertising (such as Fading Ads) and the associat ed challenges that come with it. For instance, the future trends in pricing models are more towards action-based pricing rather than impression-based pricing.
Optimization Methods for Gas and Power Markets: Theory and Cases (Applied Quantitative Finance)
by Enrico Edoli Stefano Fiorenzani Tiziano VargioluAs power and gas markets are becoming more and more mature and globally competitive, the importance of reaching maximum potential economic efficiency is fundamental in all the sectors of the value chain, from investments selection to asset optimization, trading and sales. Optimization techniques can be used in many different fields of the energy industry, in order to reduce production and financial costs, increase sales revenues and mitigate all kinds of risks potentially affecting the economic margin. For this reason the industry has now focused its attention on the general concept of optimization and to the different techniques (mainly mathematical techniques) to reach it.Optimization Methods for Gas and Power Markets presents both theoretical elements and practical examples for solving energy optimization issues in gas and power markets. Starting with the theoretical framework and the basic business and economics of power and gas optimization, it quickly moves on to review the mathematical optimization problems inherent to the industry, and their solutions – all supported with examples from the energy sector. Coverage ranges from very long-term (and capital intensive) optimization problems such as investment valuation/diversification to asset (gas and power) optimization/hedging problems, and pure trading decisions.This book first presents the readers with various examples of optimization problems arising in power and gas markets, then deals with general optimization problems and describes the mathematical tools useful for their solution. The remainder of the book is dedicated to presenting a number of key business cases which apply the proposed techniques to concrete market problems. Topics include static asset optimization, real option evaluation, dynamic optimization of structured products like swing, virtual storage or virtual power plant contracts and optimal trading in intra-day power markets. As the book progresses, so too does the level of mathematical complexity, providing readers with an appreciation of the growing sophistication of even common problems in current market practice.Optimization Methods for Gas and Power Markets provides a valuable quantitative guide to the technicalities of optimization methodologies in gas and power markets; it is essential reading for practitioners in the energy industry and financial sector who work in trading, quantitative analysis and energy risk modeling.
Optimization Methods for Gas and Power Markets: Theory and Cases (Applied Quantitative Finance)
by Stefano Fiorenzani Enrico Edoli Tiziano VargioluAs power and gas markets are becoming more and more mature and globally competitive, the importance of reaching maximum potential economic efficiency is fundamental in all the sectors of the value chain, from investments selection to asset optimization, trading and sales. Optimization techniques can be used in many different fields of the energy industry, in order to reduce production and financial costs, increase sales revenues and mitigate all kinds of risks potentially affecting the economic margin. For this reason the industry has now focused its attention on the general concept of optimization and to the different techniques (mainly mathematical techniques) to reach it. Optimization Methods for Gas and Power Markets presents both theoretical elements and practical examples for solving energy optimization issues in gas and power markets. Starting with the theoretical framework and the basic business and economics of power and gas optimization, it quickly moves on to review the mathematical optimization problems inherent to the industry, and their solutions – all supported with examples from the energy sector. Coverage ranges from very long-term (and capital intensive) optimization problems such as investment valuation/diversification to asset (gas and power) optimization/hedging problems, and pure trading decisions.
Optimization Methods in Engineering: Select Proceedings of CPIE 2019 (Lecture Notes on Multidisciplinary Industrial Engineering)
by Mohit Tyagi Anish Sachdeva Vishal SharmaThis book comprises peer-reviewed contributions from the International Conference on Production and Industrial Engineering (CPIE) 2019. This volume provides insights into the current scenario and advances in the domain of industrial and production engineering in the context of optimum value. Optimization and its applicability in various areas of production and industrial engineering like selection of designing parameters and machining parameters, decisions related to conditions of optimum process/operation parameters, behavior of response variables, facilities planning and management, transportation and supply chain management, quality engineering, reliability and maintenance, product design and development, human factors and ergonomics, service system and service management, waste management, sustainable manufacturing and operations, systems design, and performance measurement are discussed in the book. Given the range of topics covered, this book can be useful for students, researchers, and professionals interested in latest optimization techniques related to industrial and production engineering.
Optimization Methods in Finance
by Gerard Cornuejols Reha TütüncüOptimization models play an increasingly important role in financial decisions. This is the first textbook devoted to explaining how recent advances in optimization models, methods and software can be applied to solve problems in computational finance more efficiently and accurately. Chapters discussing the theory and efficient solution methods for all major classes of optimization problems alternate with chapters illustrating their use in modeling problems of mathematical finance. The reader is guided through topics such as volatility estimation, portfolio optimization problems and constructing an index fund, using techniques such as nonlinear optimization models, quadratic programming formulations and integer programming models respectively. The book is based on Master's courses in financial engineering and comes with worked examples, exercises and case studies. It will be welcomed by applied mathematicians, operational researchers and others who work in mathematical and computational finance and who are seeking a text for self-learning or for use with courses.
Optimization Modeling with Spreadsheets
by Kenneth R. BakerReflects the latest applied research and features state-of-the-art software for building and solving spreadsheet optimization modelsThoroughly updated to reflect the latest topical and technical advances in the field, Optimization Modeling with Spreadsheets, Second Edition continues to focus on solving real-world optimization problems through the creation of mathematical models and the use of spreadsheets to represent and analyze those models. Developed and extensively classroom-tested by the author, the book features a systematic approach that equips readers with the skills to apply optimization tools effectively without the need to rely on specialized algorithms.This new edition uses the powerful software package Risk Solver Platform (RSP) for optimization, including its Evolutionary Solver, which employs many recently developed ideas for heuristic programming. The author provides expanded coverage of integer programming and discusses linear and nonlinear programming using a systematic approach that emphasizes the use of spreadsheet-based optimization tools. The Second Edition also features:Classifications for the various problem types, providing the reader with a broad framework for building and recognizing optimization modelsNetwork models that allow for a more general form of mass balanceA systematic introduction to Data Envelopment Analysis (DEA)The identification of qualitative patterns in order to meaningfully interpret linear programming solutionsAn introduction to stochastic programming and the use of RSP to solve problems of this typeAdditional examples, exercises, and cases have been included throughout, allowing readers to test their comprehension of the material. In addition, a related website features Microsoft Office® Excel files to accompany the figures and data sets in the book.With its accessible and comprehensive presentation, Optimization Modeling with Spreadsheets, Second Edition is an excellent book for courses on deterministic models, optimization, and spreadsheet modeling at the upper-undergraduate and graduate levels. The book can also serve as a reference for researchers, practitioners, and consultants working in business, engineering, operations research, and management science.
Optimization Models in a Transition Economy
by Ivan V. Sergienko Mikhail Mikhalevich Ludmilla KoshlaiThis book opens new avenues in understanding mathematical models within the context of a transition economy. The exposition lays out the methods for combining different mathematical structures and tools to effectively build the next model that will accurately reflect real world economic processes. Mathematical modeling of weather phenomena allows us to forecast certain essential weather parameters without any possibility of changing them. By contrast, modeling of transition economies gives us the freedom to not only predict changes in important indexes of all types of economies, but also to influence them more effectively in the desired direction. Simply put: any economy, including a transitional one, can be controlled. This book is useful to anyone who wants to increase profits within their business, or improve the quality of their family life and the economic area they live in. It is beneficial for undergraduate and graduate students specializing in the fields of Economic Informatics, Economic Cybernetics, Applied Mathematics and Large Information Systems, as well as for professional economists, and employees of state planning and statistical organizations.
Optimization of Energy Supply Systems: Modelling, Programming and Analysis (Lecture Notes in Energy #69)
by Janet NagelThis book describes how a model for optimizing the energy supply system in Germany can be implemented. It focuses on the open energy modeling framework (Oemof) program for modeling energy supply systems. The individual elements of Oemof are described, as well as the model’s structure. The technical components of Oemof are subsequently demonstrated in mathematical calculations, along with sufficient Python code to begin basic modeling. The book will appeal to anyone with an interest in optimization models for energy supply systems, or in the mathematical description of the technical components of such systems in practical implementation, using a real example, Oemof. Thermodynamic descriptions of combustion are provided, so that readers can focus on modeling aspects. Researchers and practitioners will also find the book useful, as it expands on their knowledge of the technical components of energy supply systems, supported with detailed mathematical calculations.
Optimization of Integrated Supply Chain Planning under Multiple Uncertainty
by Juping Shao Yanan Sun Bernd NocheThe subject of this book is supply chain logistics planning optimization under multiple uncertainties, the key issue in supply chain management. Focusing on the strategic-alliance three-level supply chain, the model of supply chain logistics planning was established in terms of the market prices and the market requirements as random variables of manufactured goods with random expected value programming theory, and the hybrid intelligence algorithm solution model was designed. Aiming at the decentralized control supply chain, in which the nodes were unlimited expansion, the chance-constrained stochastic programming model was created in order to obtain optimal decision-making at a certain confidence level. In addition, the hybrid intelligence algorithm model was designed to solve the problem of supply chain logistics planning with the prices of the raw-materials supply market of the upstream enterprises and the prices of market demand for products of the downstream enterprises as random variables in the supply chain unit. Aimed at the three-stage mixed control supply chain, a logistics planning model was designed using fuzzy random programming theory with customer demand as fuzzy random variables and a hybrid intelligence algorithm solution was created. The research has significance both in theory and practice. Its theoretical significance is that the research can complement and perfect existing supply chain planning in terms of quantification. Its practical significance is that the results will guide companies in supply chain logistics planning in the uncertain environment.
Optimization of Manufacturing Processes (Springer Series in Advanced Manufacturing)
by Kapil Gupta Munish Kumar GuptaThis book provides a detailed understanding of optimization methods as they are implemented in a variety of manufacturing, fabrication and machining processes. It covers the implementation of statistical methods, multi-criteria decision making methods and evolutionary techniques for single and multi-objective optimization to improve quality, productivity, and sustainability in manufacturing. It reports on the theoretical aspects, special features, recent research and latest development in the field. Optimization of Manufacturing Processes is a valuable source of information for researchers and practitioners, as it fills the gap where no dedicated book is available on intelligent manufacturing/modeling and optimization in manufacturing. Readers will develop an understanding of the implementation of statistical and evolutionary techniques for modeling and optimization in manufacturing.
Optimization of Pharmaceutical R&D Programs and Portfolios
by Zoran AntonijevicVery little has been published on optimization of pharmaceutical portfolios. Moreover, most of published literature is coming from the commercial side, where probability of technical success (PoS) is treated as fixed, and not as a consequence of development strategy or design. In this book there is a strong focus on impact of study design on PoS and ultimately on the value of portfolio. Design options that are discussed in different chapters are dose-selection strategies, adaptive design and enrichment. Some development strategies that are discussed are indication sequencing, optimal number of programs and optimal decision criteria. This book includes chapters written by authors with very broad backgrounds including financial, clinical, statistical, decision sciences, commercial and regulatory. Many authors have long held executive positions and have been involved with decision making at a product or at a portfolio level. As such, it is expected that this book will attract a very broad audience, including decision makers in pharmaceutical R&D, commercial and financial departments. The intended audience also includes portfolio planners and managers, statisticians, decision scientists and clinicians. Early chapters describe approaches to portfolio optimization from big Pharma and Venture Capital standpoints. They have stronger focus on finances and processes. Later chapters present selected statistical and decision analysis methods for optimizing drug development programs and portfolios. Some methodological chapters are technical; however, with a few exceptions they require a relatively basic knowledge of statistics by a reader.
Optimization of Temporal Networks under Uncertainty
by Wolfram WiesemannMany decision problems in Operations Research are defined on temporal networks, that is, workflows of time-consuming tasks whose processing order is constrained by precedence relations. For example, temporal networks are used to model projects, computer applications, digital circuits and production processes. Optimization problems arise in temporal networks when a decision maker wishes to determine a temporal arrangement of the tasks and/or a resource assignment that optimizes some network characteristic (e.g. the time required to complete all tasks). The parameters of these optimization problems (e.g. the task durations) are typically unknown at the time the decision problem arises. This monograph investigates solution techniques for optimization problems in temporal networks that explicitly account for this parameter uncertainty. We study several formulations, each of which requires different information about the uncertain problem parameters.
Optimization of the Fuel Cell Renewable Hybrid Power Systems (Green Energy and Technology)
by Nicu BizonThis book offers a comprehensive review of renewable energy sources and optimization strategies in hybrid power systems (HPSs). It analyses the main issues and challenges in the renewable (REW) HPS field, particularly those using fuel cell (FC) systems as their main source of energy. It then offers innovative solutions to these issues, comparing them to solutions currently found in the literature. The book discusses optimization algorithms and energy management strategies. The focus is chiefly on FC net power maximization and fuel economy strategies based on global optimization. The last two chapters discuss energy harvesting from photovoltaic systems and how to mitigate energy variability in REW FC HPS. The main content is supplemented by numerous examples and simulations. Academics, students and practitioners in relevant industrial branches interested in REW HPS finds it of considerable interest, as a reference book or for building their own HPSs based on the examples provided.
Optimization on Solution Sets of Common Fixed Point Problems (Springer Optimization and Its Applications #178)
by Alexander J. ZaslavskiThis book is devoted to a detailed study of the subgradient projection method and its variants for convex optimization problems over the solution sets of common fixed point problems and convex feasibility problems. These optimization problems are investigated to determine good solutions obtained by different versions of the subgradient projection algorithm in the presence of sufficiently small computational errors. The use of selected algorithms is highlighted including the Cimmino type subgradient, the iterative subgradient, and the dynamic string-averaging subgradient. All results presented are new. Optimization problems where the underlying constraints are the solution sets of other problems, frequently occur in applied mathematics. The reader should not miss the section in Chapter 1 which considers some examples arising in the real world applications. The problems discussed have an important impact in optimization theory as well. The book will be useful for researches interested in the optimization theory and its applications.
Optimization Problems in Graph Theory: In Honor of Gregory Z. Gutin's 60th Birthday (Springer Optimization and Its Applications #139)
by Boris GoldengorinThis book presents open optimization problems in graph theory and networks. Each chapter reflects developments in theory and applications based on Gregory Gutin’s fundamental contributions to advanced methods and techniques in combinatorial optimization. Researchers, students, and engineers in computer science, big data, applied mathematics, operations research, algorithm design, artificial intelligence, software engineering, data analysis, industrial and systems engineering will benefit from the state-of-the-art results presented in modern graph theory and its applications to the design of efficient algorithms for optimization problems. Topics covered in this work include:· Algorithmic aspects of problems with disjoint cycles in graphs· Graphs where maximal cliques and stable sets intersect· The maximum independent set problem with special classes· A general technique for heuristic algorithms for optimization problems · The network design problem with cut constraints· Algorithms for computing the frustration index of a signed graph· A heuristic approach for studying the patrol problem on a graph· Minimum possible sum and product of the proper connection number· Structural and algorithmic results on branchings in digraphs · Improved upper bounds for Korkel--Ghosh benchmark SPLP instances
Optimization Under Stochastic Uncertainty: Methods, Control and Random Search Methods (International Series in Operations Research & Management Science #296)
by Kurt MartiThis book examines application and methods to incorporating stochastic parameter variations into the optimization process to decrease expense in corrective measures. Basic types of deterministic substitute problems occurring mostly in practice involve i) minimization of the expected primary costs subject to expected recourse cost constraints (reliability constraints) and remaining deterministic constraints, e.g. box constraints, as well as ii) minimization of the expected total costs (costs of construction, design, recourse costs, etc.) subject to the remaining deterministic constraints.After an introduction into the theory of dynamic control systems with random parameters, the major control laws are described, as open-loop control, closed-loop, feedback control and open-loop feedback control, used for iterative construction of feedback controls. For approximate solution of optimization and control problems with random parameters and involving expected cost/loss-type objective, constraint functions, Taylor expansion procedures, and Homotopy methods are considered, Examples and applications to stochastic optimization of regulators are given. Moreover, for reliability-based analysis and optimal design problems, corresponding optimization-based limit state functions are constructed. Because of the complexity of concrete optimization/control problems and their lack of the mathematical regularity as required of Mathematical Programming (MP) techniques, other optimization techniques, like random search methods (RSM) became increasingly important.Basic results on the convergence and convergence rates of random search methods are presented. Moreover, for the improvement of the – sometimes very low – convergence rate of RSM, search methods based on optimal stochastic decision processes are presented. In order to improve the convergence behavior of RSM, the random search procedure is embedded into a stochastic decision process for an optimal control of the probability distributions of the search variates (mutation random variables).
Optimization Under Uncertainty in Sustainable Agriculture and Agrifood Industry
by Víctor M. Albornoz Alejandro Mac Cawley Lluis M. Plà-AragonésThis book explores optimization under uncertainty and related applications in agriculture, sustainable supply chains and the agrifood industry. Rapid changes in the primary sector are leading to more and more industrialized structures, which require optimization methods in order to cope with today’s challenges. Addressing uncertainty in the agrifood industry may lead to more robust supply chain designs or to diversified risk. Sustainability requires interaction with the environmental or social sciences. This book bridges the gap between optimization theory, uncertainty, sustainability and primary-sector applications (mainly in the agriculture and food industry, but also fisheries, forestry and natural resources in general). Although it has been a major challenge for the operations research community, this urgently needed interdisciplinary collaboration is not adequately covered in most current curricula in applied mathematics, economics or (agronomic/industrial/forest) engineering. This book highlights research that can help fill this gap. The individual chapters cover applications of stochastic integer linear programming and multicriteria decision methods in agriculture. The topics addressed include uncertainty in areas such as the sugar cane industry, pig farming, and cold storage for perishable products. Large-scale sustainable food production is a growing concern; this book offers solutions to help meet global demand in agriculture by using and improving the methods of optimization theory and operations research.
Optimization, Variational Analysis and Applications: IFSOVAA-2020, Varanasi, India, February 2–4 (Springer Proceedings in Mathematics & Statistics #355)
by Vivek Laha Pierre Maréchal S. K. MishraThis book includes selected papers presented at the Indo-French Seminar on Optimization, Variational Analysis and Applications (IFSOVAA-2020), held at the Department of Mathematics, Institute of Science, Banaras Hindu University, Varanasi, India, from 2–4 February 2020. The book discusses current optimization problems and their solutions by using the powerful tool of variational analysis. Topics covered in this volume include set optimization, multiobjective optimization, mathematical programs with complementary, equilibrium, vanishing and switching constraints, copositive optimization, interval-valued optimization, sequential quadratic programming, bound-constrained optimization, variational inequalities, and more. Several applications in different branches of applied mathematics, engineering, economics, finance, and medical sciences have been included. Each chapter not only provides a detailed survey of the topic but also builds systematic theories and suitable algorithms to deduce the most recent findings in literature. This volume appeals to graduate students as well as researchers and practitioners in pure and applied mathematics and related fields that make use of variational analysis in solving optimization problems.
Optimization with LINGO-18: Problems and Applications
by Irfan Ali Neha GuptaThis book presents fundamental concepts of optimization problems and its real-world applications in various fields. The core concepts of optimization, formulations and solution procedures of various real-world problems are provided in an easy-to-read manner. The unique feature of this book is that it presents unified knowledge of the modelling of real-world decision-making problems and provides the solution procedure using the appropriate optimization techniques. The book will help students, researchers, and faculty members to understand the need for optimization techniques for obtaining optimal solution for the decision-making problems. It provides a sound knowledge of modelling of real-world problems using optimization techniques. It is a valuable compendium of several optimization techniques for solving real-world application problems using optimization software LINGO. The book is useful for academicians, practitioners, students and researchers in the field of OR. It is written in simple language with a detailed explanation of the core concepts of optimization techniques. Readers of this book will understand the formulation of real-world problems and their solution procedures obtained using the appropriate optimization techniques.
Optimize
by Lee OddenAttract, engage, and inspire your customers with an "Optimize and Socialize" content marketing strategyOptimize is designed to give readers a practical approach to integrating search and social media optimization with content marketing to boost relevance, visibility, and customer engagement. Companies, large and small, will benefit from the practical planning and creative content marketing tactics in this book that have been proven to increase online performance across marketing, public relations, and customer service. Learn to incorporate essential content optimization and social media engagement principles thereby increasing their ability to acquire and engage relevant customers online.Optimize provides insights from Lee Odden, one of the leading authorities on Content and Online Marketing. This book explains how to:Create a blueprint for integrated search, social media and content marketing strategyDetermine which creative tactics will provide the best results for your companyImplement search and social optimization holistically in the organizationMeasure the business value of optimized and socialized content marketingDevelop guidelines, processes and training to scale online marketing successOptimize offers a tested approach for a customer-centric and adaptive online marketing strategy that incorporates the best of content, social media marketing, and search engine optimization tactics.
Optimize Your Airbnb: The Definitive Guide To Ranking #1 In Airbnb Search
by Daniel Vroman RusteenI started writing Optimize YOUR Bnb in July 2017 while staying at an Airbnb in Estonia. I met Veronika while exploring Old Town Tallinn. When I found out Veronika was an Airbnb host, I asked to see her listing. I saw potential, but her online listing wasn't much. I told Veronika about how I optimize Airbnb listings. We agreed that I would stay at her listing for a small discount in exchange for a fully optimized Airbnb listing. As of November 2017, Veronika has 10 5-star reviews. I wrote Optimize YOUR Bnb to reach more hosts like Veronika. This book contains the culmination of my five-year experience with Airbnb from being an employee and a guest, to a host, to Superhost, and to starting an Airbnb property management company. I've hosted everything from a living room couch to a 3-story, 5-bedroom hillside mansion. The information in this book is more complete and effective than anything on the market.
Optimize Your Greatest Asset -- Your People
by Gene PeaseDrive better business strategy with practical analytics for people data Optimize Your Greatest Asset -- Your People brings advanced analytics into Human Resources, giving you a framework for optimizing human capital investments through predictive analysis. You'll learn how to transition from anecdotes and surveys to more advanced measurement techniques, and combine the data from multiple systems into a unified plan of action that improves business results. Practical examples and case studies show how these techniques are applied in real-world settings, and executives and thought leaders weigh in on how advanced analytics are informing better business decisions every day. Coverage includes the latest research on the state of current HR measurement techniques, as well as the important considerations surrounding data security and employee trust. Executives and managers alike are swimming in pools of people data, spread across multiple systems that don't talk to each other. This book shows you how to bring that data together, organize it, and turn it into useful information, and how to build your data strategy to take advantage of the wealth of available tools. Produce actionable intelligence with data from multiple systems Move beyond activity metrics and into advanced measurements Create stronger policy covering security, privacy, and ethics Achieve sophisticated HR analytics without breaking employee trust It's time for HR leaders to get over their fear of Big Data. Good data drives good business, and human capital is the biggest asset a company has. Start measuring the things that matter, and start turning those measurements into actual information that goes beyond the spreadsheet. Optimize Your Greatest Asset -- Your People shows you how to get started, and where to go from there.