Markovian Demand Inventory Models (International Series in Operations Research & Management Science)

Markovian Demand Inventory Models (International Series in Operations Research & Management Science) Review

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Markovian Demand Inventory Models (International Series in Operations Research & Management Science) Feature

This text provides a superbly researched insight into Markovian demand inventory models. The result of ten years of research, this work covers all aspects of demand inventory where they are modeled by Markov processes. Inventory management is concerned with matching supply with demand and is a central problem in Operations Management. The central problem is to find the amount to be produced or purchased in order to maximize the total expected profit, or minimize the total expected cost.

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Stochastic Processes, Optimization, and Control Theory: Applications in Financial Engineering, Queueing Networks, and Manufacturing Systems: A Volume ... in Operations Research & Management Science)

Stochastic Processes, Optimization, and Control Theory: Applications in Financial Engineering, Queueing Networks, and Manufacturing Systems: A Volume ... in Operations Research & Management Science) Review

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Stochastic Processes, Optimization, and Control Theory: Applications in Financial Engineering, Queueing Networks, and Manufacturing Systems: A Volume ... in Operations Research & Management Science) Feature

This edited volume contains 16 research articles. It presents recent and pressing issues in stochastic processes, control theory, differential games, optimization, and their applications in finance, manufacturing, queueing networks, and climate control. One of the salient features is that the book is highly multi-disciplinary. The book is dedicated to Professor Suresh Sethi on the occasion of his 60th birthday, in view of his distinguished career.

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Stochastic Modelling in Innovative Manufacturing: Proceedings, Cambridge, U.K., July 21-22, 1995 (Lecture Notes in Economics and Mathematical Systems)

Stochastic Modelling in Innovative Manufacturing: Proceedings, Cambridge, U.K., July 21-22, 1995 (Lecture Notes in Economics and Mathematical Systems) Review

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Stochastic Modelling in Innovative Manufacturing: Proceedings, Cambridge, U.K., July 21-22, 1995 (Lecture Notes in Economics and Mathematical Systems) Feature

This volume contains selected papers presented at a UK-Japanese Workshop held at Churchill College, Cambridge, July 1995. The first group of papers looks at modelling, and solution techniques that have proved useful in the operational and strategic levels of manufacturing-greedy algorithms, Markov Decision processes and Petri Nets. Further papers concentrate on operational aspects of manufacturing in an uncertain environment. The last group describes interesting problems. The volume shows that the need for stochastic modelling is an important factor in support of decision making, and that this is a growing, exciting and rewarding area of research.

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Hidden Markov Models in Finance (International Series in Operations Research & Management Science)

Hidden Markov Models in Finance (International Series in Operations Research & Management Science) Review

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Hidden Markov Models in Finance (International Series in Operations Research & Management Science) Feature

A number of methodologies have been employed to provide decision making solutions globalized markets. Hidden Markov Models in Finance offers the first systematic application of these methods to specialized financial problems: option pricing, credit risk modeling, volatility estimation and more. The book provides tools for sorting through turbulence, volatility, emotion, chaotic events – the random "noise" of financial markets – to analyze core components.

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Stochastic Models of Manufacturing Systems

Stochastic Models of Manufacturing Systems Review

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Stochastic Models of Manufacturing Systems Feature

Outlining the major issues that have to be addressed in the design and operation of each type of system, this new text explores the stochastic models of a wide range of manufacturing systems. It covers flow lines, job shops, transfer lines, flexible manufacturing systems, flexible assembly systems, cellular systems, and more. For professionals working in the area of manufacturing system modelling.

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Probabilistic and Randomized Methods for Design under Uncertainty

Probabilistic and Randomized Methods for Design under Uncertainty Review

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Probabilistic and Randomized Methods for Design under Uncertainty Feature

Probabilistic and Randomized Methods for Design under Uncertainty is a collection of contributions from the world’s leading experts in a fast-emerging branch of control engineering and operations research. The book will be bought by university researchers and lecturers along with graduate students in control engineering and operational research.

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Introduction to stochastic models in operations research

Introduction to stochastic models in operations research Review

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Interactive Operations Research with Maple: Methods and Models

Interactive Operations Research with Maple: Methods and Models Review

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Interactive Operations Research with Maple: Methods and Models Feature

This work fills an important gap in the literature by providing an important link between MAPLE and its successful use in solving problems in Operations Research (OR). The symbolic, numerical, and graphical aspects of MAPLE make this software package an ideal tool for treating certain OR problems and providing descriptive and optimization-based analyses of deterministic and stochastic models. Detailed is MAPLE's treatment of some of the mathematical techniques used in OR modeling: e.g., algebra and calculus, ordinary and partial differential equations, linear algebra, transform methods, and probability theory.

A number of examples of OR techniques and applications are presented, such as linear and nonlinear programming, dynamic programming, stochastic processes, inventory models, queueing systems, and simulation. Throughout the text MAPLE statements used in the solutions of problems are clearly explained. At the same time, technical background material is presented in a rigorous mathematical manner to reach the OR novice and professional. Numerous end-of- chapter exercises, a good bibliography and overall index at the end of the book are also included, as well as MAPLE worksheets that are easily downloadable from the author's website at www.business.mcmaster.ca/msis/profs/parlar, or from the Birkhauser website at www.birkhauser.com/cgi-win/ISBN/0-8176-4165-3.

The book is intended for advanced undergraduate and graduate students in operations research, management science departments of business schools, industrial and systems engineering, economics, and mathematics. As a self-study resource, the text can be used by researchers and practitioners who want a quick overview of MAPLE's usefulness in solving realistic OR problems that would be difficult or impossible to solve with other software packages.

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Stochastic Processes and Models

Stochastic Processes and Models Review

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Stochastic Processes and Models Feature

Stochastic Processes and Models provides a concise and lucid introduction to simple stochastic processes and models. Including numerous exercises, problems and solutions, it covers the key concepts and tools, in particular: randon walks, renewals, Markov chains, martingales, the Wiener process model for Brownian motion, and diffusion processes, concluding with a brief account of the stochastic integral and stochastic differential equations as they arise in option-pricing. The text has been thoroughly class-tested and is ideal for an undergraduate second course in probability for students of statistics, mathematics, finance and operational research.

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Stochastic Models in Reliability and Maintenance

Stochastic Models in Reliability and Maintenance Review

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Stochastic Models in Reliability and Maintenance Feature

This book contains 12 contributions on stochastic models in reliability and maintenance. Written by the leading researchers on each topic, each contribution surveys the current status on stochastic models emphasizing mathematical formulation and optimization applications. Each contribution is self-contained and has a thorough bibliography. The topics include renewal processes, semi-Markov processes, Markovian deterioration models, maintenance and replacement models, software reliability models and Monte-Carlo simulation. This book provides researchers, reliability engineers and graduate students with the current status of the field and future developments of the subject.

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