Описание: Thistextbook approaches optimization from a multi-aspect, multi-criteria perspective.By using a Multiple Criteria Decision Making (MCDM) approach, it avoids thelimits and oversimplifications that can come with optimization models with onecriterion. The book is presented in a concise form, addressing how to solve decisionproblems in sequences of intelligence, modelling, choice and review phases,often iterated, to identify the most preferred decision variant. The approachtaken is human-centric, with the user taking the final decision is a sole andsovereign actor in the decision making process. To ensure generality, noassumption about the Decision Maker preferences or behavior is made. The presentationof these concepts is illustrated by numerous examples, figures, and problems tobe solved with the help of downloadable spreadsheets. This electroniccompanion contains models of problems to be solved built in Excel spreadsheetfiles.Optimizationmodels are too often oversimplifications of decision problems met in practice.For instance, modeling company performance by an optimization model in whichthe criterion function is short-term profit to be maximized, does not fullyreflect the essence of business management. The company’s managing staff isaccountable not only for operational decisions, but also for actions whichshall result in the company ability to generate a decent profit in the future.This calls for management decisions and actions which ensure short-termprofitability, but also maintaining long-term relations with clients,introducing innovative products, financing long-term investments, etc. Each ofthose additional, though indispensable actions and their effects can be modeledseparately, case by case, by an optimization model with a criterion functionadequately selected. However, in each case the same set of constraintsrepresents the range of company admissible actions. The aim and the scope ofthis textbook is to present methodologies and methods enabling modeling of suchactions jointly.
This book provides a broad coverage of the recent advances in robustness analysis in decision aiding, optimization, and analytics. It offers a comprehensive illustration of the challenges that robustness raises in different operations research and management science (OR/MS) contexts and the methodologies proposed from multiple perspectives. Aside from covering recent methodological developments, this volume also features applications of robust techniques in engineering and management, thus illustrating the robustness issues raised in real-world problems and their resolution within advances in OR/MS methodologies.
Robustness analysis seeks to address issues by promoting solutions, which are acceptable under a wide set of hypotheses, assumptions and estimates. In OR/MS, robustness has been mostly viewed in the context of optimization under uncertainty. Several scholars, however, have emphasized the multiple facets of robustness analysis in a broader OR/MS perspective that goes beyond the traditional framework, seeking to cover the decision support nature of OR/MS methodologies as well. As new challenges emerge in a “big-data'” era, where the information volume, speed of flow, and complexity increase rapidly, and analytics play a fundamental role for strategic and operational decision-making at a global level, robustness issues such as the ones covered in this book become more relevant than ever for providing sound decision support through more powerful analytic tools.
Автор: Anita Sch?bel Название: Optimization in Public Transportation ISBN: 1441941061 ISBN-13(EAN): 9781441941060 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book develops models, results and algorithms for optimizing public transportation from a customer-oriented viewpoint. An appendix summarizes some of the basics of optimization needed to interpret the material in the book.
Описание: This contributed volume presents a collection of materials on supply chain management including industry-based case studies addressing petrochemical, pharmaceutical, manufacturing and reverse logistics topics. Moreover, the book covers sustainability issues, as well as optimization approaches. The target audience comprises academics, industry managers, and practitioners in the field of supply chain management, being the book also beneficial for graduate students
Many real-world systems in engineering are composed of multi-state components that have different performance levels and several failure modes. These have effects on the entire system's performance.
Most books on reliability theory are devoted to traditional binary models that only allow a system either to function perfectly or fail completely.
The Universal Generating Function in Reliability Analysis and Optimization is the first book that gives a comprehensive description of the universal generating function technique and its applications in both binary and multi-state system reliability analysis.
Features:
an introduction to the basic tools used in multi-state system reliability and optimisation;
applications of the universal generating function in the most widely used multi-state systems;
several examples of how the universal generating function can be adapted to different systems in mechanical, industrial and software engineering
The Universal Generating Function in Reliability Analysis and Optimization will be of value to all those interested in multi-state systems in industrial, electrical and nuclear engineering.
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