CONCLUSIONS
STOCHASTIC PROGRAMS CAN BE:
- LINEAR, NONLINEAR, INTEGER PROGRAMS
- CONTINUOUS OR DISCRETE R.V.’S
- OF SIGNIFICANT VALUE (VSS) OVER DETERMINISTIC or STATIC MODELS
RANDOMNESS =>
- VALUE OF MODELING
- DIFFICULTY IN EVALUATING OBJECTIVES
- MOTIVATION FOR APPROXIMATION
SOLUTIONS
- DECOMPOSITION FOR LINEAR PROBLEMS
- SPEEDUPS OF ORDERS OF MAGNITUDE
- LAGRANGIAN METHODS WITH GOOD RESULTS ON INTEGER PROBLEMS