Long-run planning for linear discrete systems, with clear methods and practical insights.
This book provides a structured look at optimizing actions over an infinite horizon in linear, discrete-time models. It blends theory with process ideas to help you understand feasibility, stability, and optimal control in dynamic systems. The discussion emphasizes how stationarity and steady-state reasoning can guide short- and long-term decisions in a practical setting.
- Learn how to frame and analyze feasibility for infinite sequences of decisions.
- Explore the dynamic programming approach and the role of fixed-point methods in finding optimal returns.
- See how convexity, contraction mappings, and stationary strategies lead to computable solutions.
- Review a numerical example that illustrates how to derive a return function and optimal strategy.
Ideal for readers of engineering, operations research, and economic planning who want a rigorous yet accessible treatment of long-run decision making in linear systems.