Transcription of Introduction to Stochastic Programming
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1 CUSTOM Conference, December 20011 Introduction to Stochastic ProgrammingJohn R. BirgeNorthwestern UniversityCUSTOM Conference, December 20012 Outline Overview Examples Vehicle Allocation Financial planning Manufacturing Methods View ahead2 CUSTOM Conference, December 20013 Overview Stochastic optimization Traditional Small problems Impractical Current Integrate with large-scale optimization ( Stochastic Programming ) Practical examples Expanding rapidlyCUSTOM Conference, December 20014 Vehicle Allocation Decision: How to position empty freight cars?NOW:AB5 cars0 carsDAY 1:DAY 2:ABABDEMAND:DAY 1: B to A:Mean Value=2 DAY 1: A to B:Mean Value=2??223 CUSTOM Conference, December 20015 Maximize:Revenue-Cost MOVE TWO EMPTY CARS FROM A to BNOW:AB5 cars0 carsDAY 1:DAY 2:ABABRESULT:Net 2: A to B; Net 2: B to ATOTAL(MV) = 43122 Parameters: COST: per empty car from A to BREVENUE: per full car from A to B222 Vehicle Allocation: Mean Value SolutionCUSTOM Conference, December 20016 Find: Expected(Revenue-Cost) MOVE TwoEMPTY CARS FROM A to BNOW:AB5 cars0 carsDAY 1:DAY 2:ABABE xpected Value:Net 2: A to B; Net 2: B to A ( 2/3)-1: B to A ( 1/3)TOTAL (EMV): 323 ( )2 Suppose: Demand is Random (Expectationfrom A to B=2) 0 from A to B with prob.
Introduction to Stochastic Programming John R. Birge Northwestern University CUSTOM Conference, December 2001 2 Outline •Overview •Examples • Vehicle Allocation • Financial planning • Manufacturing • Methods • View ahead. 2 CUSTOM Conference, December 2001 3 Overview • Stochastic optimization
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An Introduction to Stochastic Epidemic Models, Introduction, Stochas-tic, Stochastic, AN INTRODUCTION TO COMPUTATIONAL STOCHASTIC, AN INTRODUCTION TO COMPUTATIONAL STOCHASTIC PDES, An Introduction to Stochastic PDEs, An Introduction to Stochastic Unit Root, Brief Introduction to Stochastic Calculus, Introduction to probability models, An introduction, Stochastic Programming: introduction and examples, Introduction to Stochastic Processes MATH, INTRODUCTION TO STOCHASTIC PROCESSES. MARKOV