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. Decision & Control in Management Science is an excellent reference covering methodological issues and applications in operations research, optimal control, and dynamic games.

Study of operational research in management - includes sections on decision making and control, simulation, automation and the outcome for industry and government.

"This book presents an application and demonstration of a new mathematical technique for descriptions of complex systems"--Provided by publisher.

This book treats stochastic control theory and its applications in management. The main numerical techniques necessary for such applications are presented. Several advanced topics leading to optimal processes are dismissed. The book also considers the theory of some stochastic control processes and several applications to illustrate the ideas.

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The focus of this book is on using data and spreadsheet models effectively for the analysis of business problems and decision making. Included are discussions of building good spreadsheet models; data collection, visualization, and statistical analysis; forecasting; optimization using Excel Solver; decision and risk analysis; and simulation using Crystal Ball add-in for Excel and Arena BE. The principal focus is on gaining insight and intuition for better decisions, with applications in operations planning, finance, and marketing.

In order to ensure the criteria for monitoring and managing the various problems and design for decision control, a mathematical description of exact human knowledge is required for the management of adaptive and complex systems. Decision Control, Management, and Support in Adaptive and Complex Systems: Quantitative Models presents an application and demonstration of a new mathematical technique for descriptions of complex systems. This comprehensive collection contains scientific results in the field of contemporary approaches to adaptive decision making that is essential for researchers, scholars, and students alike.