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Analyzing the quality of the expected value solution in stochastic programming

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Analyzing the quality of the expected value solution in stochastic programming. / Maggioni, Francesca; Wallace, Stein W.
In: Annals of Operations Research, Vol. 200, No. 1, 11.2012.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Maggioni F, Wallace SW. Analyzing the quality of the expected value solution in stochastic programming. Annals of Operations Research. 2012 Nov;200(1). Epub 2010 Nov 6. doi: 10.1007/s10479-010-0807-x

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Maggioni, Francesca ; Wallace, Stein W. / Analyzing the quality of the expected value solution in stochastic programming. In: Annals of Operations Research. 2012 ; Vol. 200, No. 1.

Bibtex

@article{168ef7accf93466ca9aea1131f050b28,
title = "Analyzing the quality of the expected value solution in stochastic programming",
abstract = "Stochastic programs are usually hard to solve when applied to real-world problems; a common approach is to consider the simpler deterministic program in which random parameters are replaced by their expected values, with a loss in terms of quality of the solution. The Value of the Stochastic Solution—VSS—is normally used to measure the importance of using a stochastic model. But what if VSS is large, or expected to be large, but we cannot solve the relevant stochastic program? Shall we just give up? In this paper we investigate very simple methods for studying structural similarities and differences between the stochastic solution and its deterministic counterpart. The aim of the methods is to find out, even when VSS is large, if the deterministic solution carries useful information for the stochastic case. It turns out that a large VSS does not necessarily imply that the deterministic solution is useless for the stochastic setting. Measures of the structure and upgradeability of the deterministic solution such as the loss using the skeleton solution and the loss of upgrading the deterministic solution will be introduced and basic inequalities in relation to the standard VSS are presented and tested on different cases.",
keywords = "Stochastic programming , Expected value problem , Value of stochastic solution, Quality of deterministic solution , Skeleton solution , Upgradeability of deterministic solution",
author = "Francesca Maggioni and Wallace, {Stein W}",
year = "2012",
month = nov,
doi = "10.1007/s10479-010-0807-x",
language = "English",
volume = "200",
journal = "Annals of Operations Research",
issn = "0254-5330",
publisher = "Springer",
number = "1",

}

RIS

TY - JOUR

T1 - Analyzing the quality of the expected value solution in stochastic programming

AU - Maggioni, Francesca

AU - Wallace, Stein W

PY - 2012/11

Y1 - 2012/11

N2 - Stochastic programs are usually hard to solve when applied to real-world problems; a common approach is to consider the simpler deterministic program in which random parameters are replaced by their expected values, with a loss in terms of quality of the solution. The Value of the Stochastic Solution—VSS—is normally used to measure the importance of using a stochastic model. But what if VSS is large, or expected to be large, but we cannot solve the relevant stochastic program? Shall we just give up? In this paper we investigate very simple methods for studying structural similarities and differences between the stochastic solution and its deterministic counterpart. The aim of the methods is to find out, even when VSS is large, if the deterministic solution carries useful information for the stochastic case. It turns out that a large VSS does not necessarily imply that the deterministic solution is useless for the stochastic setting. Measures of the structure and upgradeability of the deterministic solution such as the loss using the skeleton solution and the loss of upgrading the deterministic solution will be introduced and basic inequalities in relation to the standard VSS are presented and tested on different cases.

AB - Stochastic programs are usually hard to solve when applied to real-world problems; a common approach is to consider the simpler deterministic program in which random parameters are replaced by their expected values, with a loss in terms of quality of the solution. The Value of the Stochastic Solution—VSS—is normally used to measure the importance of using a stochastic model. But what if VSS is large, or expected to be large, but we cannot solve the relevant stochastic program? Shall we just give up? In this paper we investigate very simple methods for studying structural similarities and differences between the stochastic solution and its deterministic counterpart. The aim of the methods is to find out, even when VSS is large, if the deterministic solution carries useful information for the stochastic case. It turns out that a large VSS does not necessarily imply that the deterministic solution is useless for the stochastic setting. Measures of the structure and upgradeability of the deterministic solution such as the loss using the skeleton solution and the loss of upgrading the deterministic solution will be introduced and basic inequalities in relation to the standard VSS are presented and tested on different cases.

KW - Stochastic programming

KW - Expected value problem

KW - Value of stochastic solution

KW - Quality of deterministic solution

KW - Skeleton solution

KW - Upgradeability of deterministic solution

U2 - 10.1007/s10479-010-0807-x

DO - 10.1007/s10479-010-0807-x

M3 - Journal article

VL - 200

JO - Annals of Operations Research

JF - Annals of Operations Research

SN - 0254-5330

IS - 1

ER -