Modern Optimization Methods for Decision Making Under Risk and Uncertainty [Paperback]

Preface. Optimization of Complex Simulation Models with Stochastic Gradient Methods. Linking Catastrophe Modeling and Stochastic Optimization techniques for Integrated Catastrophe Risk Analysis and Management. Authentication for Coalition Groups. Robust Constructions of Risk Measures for Optimization under Uncertainty. On Minimum Length Confidence Intervals. The independence number of the generalized wheel graphs W^p2k+1. Approximations for Estimating Some Options Using the Inverse of the Laplace Transform. A Nash Equilibrium based Model of Agents Coordination through Revenue Sharing and Applications to Telecommunications. Nash Equilibrium and its Modern Applications. On the Vector Optimal Control of Risk Processes. The Type-Variety Principle in Ensuring the Reliability, Safety and Resilience of Critical Infrastructures. Informational Extended Games and Decision-Making Processes at Risk and Uncertainty. Energy Production and Storage Investments and Operation Planning Involving Variable Renewable Energy Sources: A Two-Stage Stochastic Optimization Model with Rolling Time Horizon and Random Stopping Time. How the Market Power of Electricity Suppliers and a Carbon Price Together Affect the Restructured Electricity Markets. Safety of Water Resources of River Basin. Optimization problems for retrial queues with unreliable server.

The book comprises original articles on topical issues in risk theory, rational decision making, statistical decisions, and control of stochastic systems.

The book comprises original articles on topical issues of risk theory, rational decision making, statistical decisions, and control of stochastic systems. The articles are the outcome of a series international projects involving the leading scholars in the field of modern stochastic optimization and decision making. The structure of stochastic optimization solvers is described. The solvers in general implement stochastic quasil#&