PrefaceⅠ OPTIMIZATION MODELS1 ONE VARIABLE OPTIMIZATION 1.1 The Five-Step Method 1.2 Sensitivity Analysis 1.3 Sensitivity and Robustness 1.4 Exercises2 MULTIVARIABLE OPTIMIZATION 2.1 Unconstrained Optimization 2.2 Lagrange Multipliers 2.3 Sensitivity Analysis and Shadow Prices 2.4 Exercises3 COMPUTATIONAL METHODS FOR OPTIMIZATION 3.1 One Variable Optimization 3.2 Multivariable Optimization 3.3 Linear Programming 3.4 Discrete Optimization 3.5 ExercisesⅡ DYNAMIC MODELS4 INTRODUCTION TO DYNAMIC MODELS 4.1 Steady State Analysis 4.2 Dynamical Systems 4.3 Discrete Time Dynamical Systems 4.4 Exercises5 ANALYSIS OF DYNAMIC MODELS 5.1 Eigenvalue Methods 5.2 Eigenvalue Methods for Discrete Systems 5.3 Phase Portraits 5.4 Exercises6 SIMULATION OF DYNAMIC MODELS 6.1 Introduction to Simulation 6.2 Continuous-Time Models 6.3 The Euler Method 6.4 Chaos and Fractals 6.5 ExercisesⅢ PROBABILITY MODELS7 INTRODUCTION TO PROBABILITY MODELS 7.1 Discrete Probability Models 7.2 Continuous Probability Models 7.3 Introduction to Statistics 7.4 Diffusion 7.5 Exercises8 STOCHASTIC MODELS 8.1 Markov Chains 8.2 Markov Processes 8.3 Linear Regression 8.4 Time Series 8.5 Exercises9 SIMULATION OF PROBABILITY MODELS 9.1 Monte Carlo Simulation 9.2 The Markov Property 9.3 Analytic Simulation 9.4 ExercisesAfterwordIndex