Stochastic Analysis, Control, Optimization And Applications

An outgrowth of the sixth conference on “Mathematical Methods in Reliability: Theory, Methods, and Applications,” this book is a selection of invited chapters, all of which deal with various aspects of mathematical and statistical models and methods in reliability.

Decision & Control in Management Science analyzes emerging decision problems in the management and engineering sciences. It is divided into five parts. The first part explores methodological issues involved in the optimization of deterministic and stochastic dynamical systems. The second part describes approaches to the model energy and environmental systems and draws policy implications related to the mitigation of pollutants. The third part applies quantitative techniques to problems in finance and economics, such as hedging of options, inflation targeting, and equilibrium asset pricing. The fourth part considers a series of problems in production systems. Optimization methods are put forward to provide optimal policies in areas such as inventory management, transfer-line, flow-shop and other industrial problems. The last part covers game theory. Chapters range from theoretical issues to applications in politics and interactions in franchising systems.

Researchers and practitioners in computer science, optimization, operations research and mathematics will find this book useful as it illustrates optimization models and solution methods in discrete, non-differentiable, stochastic, and nonlinear optimization. Contributions from experts in optimization are showcased in this book showcase a broad range of applications and topics detailed in this volume, including pattern and image recognition, computer vision, robust network design, and process control in nonlinear distributed systems.