Kategoria BISAC: Business & Economics >> Operations Research

Under intense scrutiny for the last few decades, Multiple Objective Decision Making (MODM) has been useful for dealing with the multiple-criteria decisions and planning problems associated with many important applications in fields including management science, engineering design, and transportation. Rough set theory has also proved to be an effective mathematical tool to counter the vague description of objects in fields such as artificial intelligence, expert systems, civil engineering, medical data analysis, data mining, pattern recognition, and decision theory.

Rough...

* Provides a broad overview of modeling approaches and solution methodologies for addressing inventory problems, particularly the management of high cost, low demand rate service parts found in multi-echelon settings

* The text may be used in a variety of courses for first-year graduate students or senior undergraduates, or as a reference for researchers and practitioners

* A background in stochastic processes and optimization is assumed

The Analytic Network Process (ANP) developed by Thomas Saaty in his work on multicriteria decision making applies network structures with dependence and feedback to complex decision making. This book is a selection of applications of ANP to economic, social and political decisions, and also to technological design. The chapters comprise contributions of scholars, consultants and people concerned about the outcome of certain important decisions who applied the Analytic Network Process to determine the best outcome for each decision from among several potential outcomes. The ANP is a...

Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. MDPs can be used to model and solve dynamic decision-making problems that are multi-period and occur in stochastic circumstances. There are three basic branches in MDPs: discrete-time MDPs, continuous-time MDPs and semi-Markov decision processes. Starting from these three branches, many generalized MDPs models have been applied to various practical problems. These models include partially observable MDPs, adaptive MDPs, MDPs in stochastic environments, and MDPs with multiple...

Network Science, Nonlinear Science and Infrastructure Systems has been written by leading scholars in these areas. Its express purpose is to develop common theoretical underpinnings to better solve modern infrastructural problems. It is felt by many who work in these fields that many modern communication problems, ranging from transportation networks to telecommunications, Internet, supply chains, etc., are fundamentally infrastructure problems. Moreover, these infrastructure problems would benefit greatly from a confluence of theoretical and methodological work done with the areas of...

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.

DYNAMIC FLEET MANAGEMENT will focus on real time management of a distribution system. This means that when a dynamic event occurs within the distribution chain, action must be taken in "real-time." The book will integrate the latest results in system design, algorithm development and system implementation, to capture the state-of-the art research and application trends. While much of the research in this area of transportation problems have almost exclusively concentrated on carrying out static plans on optional distribution conditions, this book will examine those problems when some...

Metaheuristics has grown and continues to grow steadily. Seen both from the technical point of view and from the application-oriented side, these optimization tools have established their value in a remarkable story of success. Researchers have demonstrated the ability of these methods to solve hard combinatorial problems of practical sizes within reasonable computational time.

Highlighted in METAHEURISTICS: Progress in Complex Systems Optimization are the recent developments made in the area of Simulated Annealing, Path Relinking, Scatter Search, Tabu Search, Variable...

In the past 30 years, commercial transport traffic has more than doubled in both Europe and North America. Asian commercial transport traffic over this period of time has likely increased even more. Traffic jams are routine and they can happen in any segment of the highway system at any time. Moreover, manufacturing companies increasingly apply just-in-time practices in order to cut down inventory costs. As any mismatch between supply and demand can result into significant disturbances of manufacturing processes, just-in-time practices necessitate punctual, reliable, and flexible...

Besides scheduling problems for single and parallel machines and shop scheduling problems, this book covers advanced models involving due-dates, sequence dependent changeover times and batching. Discussion also extends to multiprocessor task scheduling and problems with multi-purpose machines. Among the methods used to solve these problems are linear programming, dynamic programming, branch-and-bound algorithms, and local search heuristics. The text goes on to summarize complexity results for different classes of deterministic scheduling problems.