Dynamic Systems Modeling and Optimal Control Applications in Management Science

Optimization of a dynamic system has immense importance in Management Science. Both discrete time and continuous time optimal control systems are very useful instruments in this regard. To simulate uncertainty regarding the structure and components of a dynamic system, a number of novel methods are introduced which can alter the standard treatment of a dynamic system. Dynamic Systems Modelling and Optimal Control explores the applications of oil field development, energy system modelling, resource modelling, time varying control of dynamic system of national economy, and investment planning.

Dipak Basu is Professor in International Economics in Nagasaki University, Japan. Previously he was lecturer in the Institute of Agricultural Economics at Oxford University, Research Officer in the Department of Applied Economics at Cambridge University, Senior Economist in Charge of the Middle East & Africa division of Standard & Poor, and Senior Economist in the Ministry of Foreign Affairs of Saudi Arabia. He is a member of the editorial board of International Journal of Decision Sciences, Risk and Management and was the editor of the Middle East & Africa Review. He has received his PhD from the University of Birmingham, UK.

Victoria W. Miroshnik is Associate Professor in Management, Tokyo International University, Japan. She was awarded the Adam Smith Research Fellowship from the University of Glasgow, UK and was previously Associate Professor in Management at Keimyung University, South Korea; American University Dubai; Ritsumeikan Asia-Pacific University, Japan; and a psychologist in the Military Academy of USSR in Tbilisi, Georgia.

Introduction
1. Optimal Control of Dynamic Systems 
2. Optimal Planning with Exhaustible Resource
3. Management of Oil Field Development 
4. Control of Energy System 
5. Control System for Investment Planning
6. National Economic Management with Stochastic Optimal Control: Simulations Over History 
7. Anticipations and Time Varying Modeling in Adaptive Control System
8. Dynamics of Information and Resource Management
Conclusion