A note on probability assignments in estimating the time to solve linear programs

B. R. Feiring; Edwin Tai Chiu Cheng; C. R. Bector

doi:10.1016/0893-9659(91)90171-Q

A note on probability assignments in estimating the time to solve linear programs

B. R. Feiring, Edwin Tai Chiu Cheng, C. R. Bector

Research output: Journal article publication › Journal article › Academic research › peer-review

Abstract

Exterior-point linear programming algorithms have been modelled as a Markov chain in order to model the transitions between extreme points. This approach is useful in that it ultimately provides a confidence interval on the expected number of pivots.This paper provides an alternative to the assumption of equally likelihood from one state to animproved state. Other considerations such as cycling and multiple solutions are considered.

Original language	English
Pages (from-to)	65-67
Number of pages	3
Journal	Applied Mathematics Letters
Volume	4
Issue number	2
DOIs	https://doi.org/10.1016/0893-9659(91)90171-Q
Publication status	Published - 1 Jan 1991
Externally published	Yes

ASJC Scopus subject areas

Applied Mathematics

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10.1016/0893-9659(91)90171-Q

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title = "A note on probability assignments in estimating the time to solve linear programs",

abstract = "Exterior-point linear programming algorithms have been modelled as a Markov chain in order to model the transitions between extreme points. This approach is useful in that it ultimately provides a confidence interval on the expected number of pivots.This paper provides an alternative to the assumption of equally likelihood from one state to animproved state. Other considerations such as cycling and multiple solutions are considered.",

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AB - Exterior-point linear programming algorithms have been modelled as a Markov chain in order to model the transitions between extreme points. This approach is useful in that it ultimately provides a confidence interval on the expected number of pivots.This paper provides an alternative to the assumption of equally likelihood from one state to animproved state. Other considerations such as cycling and multiple solutions are considered.

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A note on probability assignments in estimating the time to solve linear programs

Abstract

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