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Stochastic Programming

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Cover of 'Stochastic Programming'

Table of Contents

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    Book Overview
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    Chapter 1 Linear Programming Under Uncertainty
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    Chapter 2 A Probabilistic Lower Bound for Two-Stage Stochastic Programs
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    Chapter 3 Simulation-Based Optimality Tests for Stochastic Programs
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    Chapter 4 Stochastic Decomposition and Extensions
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    Chapter 5 Barycentric Bounds in Stochastic Programming: Theory and Application
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    Chapter 6 Stochastic Programming Approximations Using Limited Moment Information, with Application to Asset Allocation
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    Chapter 7 Stability and Scenario Trees for Multistage Stochastic Programs
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    Chapter 8 Risk Aversion in Two-Stage Stochastic Integer Programming
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    Chapter 9 Portfolio Optimization with Risk Control by Stochastic Dominance Constraints
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    Chapter 10 Single-Period Mean–Variance Analysis in a Changing World
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    Chapter 11 Mean–Absolute Deviation Model
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    Chapter 12 Multistage Financial Planning Models: Integrating Stochastic Programs and Policy Simulators
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    Chapter 13 Growth–Security Models and Stochastic Dominance
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    Chapter 14 Production Planning Under Supply and Demand Uncertainty: A Stochastic Programming Approach
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    Chapter 15 Global Climate Decisions Under Uncertainty
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    Chapter 16 Control of Diffusions via Linear Programming
Attention for Chapter 11: Mean–Absolute Deviation Model
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