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Dynamic Management Decision and Stochastic Control Processes cover

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.


Contents:
  • Prediction Theory:
    • Approach of N Levinson, Dynamic Programming Approach, Comparison
  • Invariant Imbedding And Identification Of Aquifer Parameters:
    • Quasi-linearization, Invariant Imbedding, Comparison between the Two Methods
  • Information And Decision In Optimal Inventory Processes:
    • Principle of Balance, Inventory Systems Design, Numerical Example
  • Optimal Inventory Processes With A Delay Delivery:
    • Stability Theorems, Analytic Consideration, Simulation
  • Optimal Capacity Expansion Of The System:
    • Deterministic Model, Probabilistic Model, Constrained Water Pricing
  • Optimal Pumping Policies For Ground Water:
    • Conjunctive Surface and Ground Water, An Empirical Application, Turnpike Horizons
  • Stochastic Control Processes And Management Science:
    • Mathematical Formulation, Fuzzy Control Processes, Applications, Numerical Example
  • Fuzzy Control Processes:
    • Mathematical Model, Existence and Uniqueness Theorem, Optimal Policy, Numerical Example
  • Adaptive Control Processes:
    • Optimal Policy for Some Non-stationary Stochastic Control Processes, Optimal Policy for an Adaptive Control Process
  • Stochastic Bang-Bang Control Processes:
    • Mathematical Model, Optimal Policy
  • Control Chart And Stochastic Control Processes:
    • Statistical Quality Control Processes
    • Mathematical Formulation, Optimal Control of Linear Systems, Problem on Quality Control in a Food Company
  • The Stochastic Bang-Bang Control:
    • Minimization of Membership Function, Optimal Policy, Combined Use of Runs
  • Economic Criterion and Probabilistic Criterion:
    • Problem Definition, Results

Readership: Systems scientists, management scientists, engineers, people working in operations research, cybernetics & control theory and those interested in learning about new directions in decision making and control.