Stochastic Programming: The State of the Art In Honor of George B. Dantzig (International Series in Operations Research & Management Science Book 150)

From the Preface... The preparation of this book started in 2004, when George B. Dantzig and I, following a long-standing invitation by Fred Hillier to contribute a volume to his International Series in Operations Research and Management Science, decided finally to go ahead with editing a volume on stochastic programming. The field of stochastic programming (also referred to as optimization under uncertainty or planning under uncertainty) had advanced significantly in the last two decades, both theoretically and in practice. George Dantzig and I felt that it would be valuable to showcase some of these advances and to present what one might call the state-of- the-art of the field to a broader audience. We invited researchers whom we considered to be leading experts in various specialties of the field, including a few representatives of promising developments in the making, to write a chapter for the volume. Unfortunately, to the great loss of all of us, George Dantzig passed away on May 13, 2005. Encouraged by many colleagues, I decided to continue with the book and edit it as a volume dedicated to George Dantzig. Management Science published in 2005 a special volume featuring the “Ten most Influential Papers of the first 50 Years of Management Science.” George Dantzig’s original 1955 stochastic programming paper, “Linear Programming under Uncertainty,” was featured among these ten. Hearing about this, George Dantzig suggested that his 1955 paper be the first chapter of this book. The vision expressed in that paper gives an important scientific and historical perspective to the book. Gerd Infanger Front Matter....Pages i-xxiii Linear Programming Under Uncertainty....Pages 1-11 A Probabilistic Lower Bound for Two-Stage Stochastic Programs....Pages 13-35 Simulation-Based Optimality Tests for Stochastic Programs....Pages 37-55 Stochastic Decomposition and Extensions....Pages 57-66 Barycentric Bounds in Stochastic Programming: Theory and Application....Pages 67-96 Stochastic Programming Approximations Using Limited Moment Information, with Application to Asset Allocation....Pages 97-138 Stability and Scenario Trees for Multistage Stochastic Programs....Pages 139-164 Risk Aversion in Two-Stage Stochastic Integer Programming....Pages 165-187 Portfolio Optimization with Risk Control by Stochastic Dominance Constraints....Pages 189-211 Single-Period Mean–Variance Analysis in a Changing World....Pages 213-237 Mean–Absolute Deviation Model....Pages 239-255 Multistage Financial Planning Models: Integrating Stochastic Programs and Policy Simulators....Pages 257-275 Growth–Security Models and Stochastic Dominance....Pages 277-296 Production Planning Under Supply and Demand Uncertainty: A Stochastic Programming Approach....Pages 297-315 Global Climate Decisions Under Uncertainty....Pages 317-327 Control of Diffusions via Linear Programming....Pages 329-353 Back Matter....Pages 355-362