Models and model value in stochastic programming
نویسندگان
چکیده
منابع مشابه
Models and model value in stochastic programming
Finding optimal decisions often involves the consideration of certain random or unknown parameters. A standard approach is to replace the random parameters by the expectations and to solve a deterministic mathematical program. A second approach is to consider possible future scenarios and the decision that would be best under each of these scenarios. The question then becomes how to choose amon...
متن کاملStochastic Facilities location Model by Using Stochastic Programming
Finding the location for plans like factories or warehousesfor any organization is an important and strategic decision. Costs oftransportation which are the main part of the price of the goods, is thefunction of the location of these projects. to find the optimum locationof these projects, there have been various methods proposed which areusually defined (not random). In reality and in dealing ...
متن کاملStochastic Programming Models in Energy
We give the reader a tour of good energy optimization models that explicitly deal with uncertainty. The uncertainty usually stems from unpredictability of demand and/or prices of energy, or from resource availability and prices. Since most energy investments or operations involve irreversible decisions, a stochastic programming approach is meaningful. Many of the models deal with electricity in...
متن کاملDynamic Inventory Models and Stochastic Programming
A wide class of single-product, dynamic inventory problems with convex cost functions and a finite horizon is investigated as a stochastic programming problem. When demands have finite discrete distribution functions, we show that the problem can be substantially reduced in size to a linear program with upper-bounded variables. Moreover,, we show that the reduced problem has a network represent...
متن کاملRamsey Stochastic Model via Multistage Stochastic Programming
Ramsey model belongs to “classical” economic dynamic models. It has been (1928) originally constructed (with a farmer’s interpretation) in a deterministic discrete setting. To solve it Lagrangean or dynamic programming techniques can be employed. Later, this model has been generalized to a stochastic version. Time horizon in the original deterministic model as well as in modified stochastic one...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Annals of Operations Research
سال: 1995
ISSN: 0254-5330,1572-9338
DOI: 10.1007/bf02031741