BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Two-Stage Stochastic Linear Programming with Recourse: A Characterization of Local Regions Using Response Surface Methodology

Two-Stage Stochastic Linear Programming with Recourse: A Characterization of Local Regions Using Response Surface Methodology

Two-Stage Stochastic Linear Programming with Recourse: A Characterization of
Stock photo: cover may vary

Two-Stage Stochastic Linear Programming with Recourse: A Characterization of Local Regions Using Response Surface Methodology Paperback - 2012

by Mills, David T

Add to wish list
  • Used
  • Good
  • Paperback
Used - Good

Description

paperback. Good. Access codes and supplements are not guaranteed with used items. May be an ex-library book.
Ask the seller a question Add to wish list
A$144.16
Free Delivery within USA
Standard delivery: 7 to 14 days
More delivery options
Dropship order
Ships from Bonita (California, United States)

Details

  • Title Two-Stage Stochastic Linear Programming with Recourse: A Characterization of Local Regions Using Response Surface Methodology
  • Author Mills, David T
  • Binding Paperback
  • Condition Used - Good
  • Pages 94
  • Volumes 1
  • Language ENG
  • Publisher Biblioscholar
  • Publication date 2012-10-03
  • Illustrated Yes
  • Bookseller's Inventory # 1249586763.G
  • ISBN 9781249586760 / 1249586763
  • Weight 0.4 lbs (0.18 kg)
  • Dimensions 9.69 x 7.44 x 0.19 in (24.61 x 18.90 x 0.48 cm)
  • Category Education / Teaching
  • Quantity available 1

About Bonita California, United States

Biblio member since 2020

Terms of Sale: 30 day return guarantee, with full refund including original shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

Browse books from Bonita

Reader reviews for Two-Stage Stochastic Linear Programming with Recourse: A Characterization of Local Regions Using Response Surface Methodology

From the publisher

The LP recourse problem applies to two-stage optimization problems where uncertainty in resource availability of the second stage hinders informed decision making. The recourse function affords a way to compensate "later" for an error in prediction "now." The literature provides a rich body of work on the optimization of such problems, but little research has been accomplished regarding the characterization of the surface in the local region of optimality, in particular sensitivity analysis. A decision maker faced with considerations other than the modeled objective function must be presented with a way to estimate the impact of operating at non-optimal decision variable values. This work develops and demonstrates a technique for characterizing the surface using response surface methodology. Specifically, the flexibility and utility of RSM techniques applied to this class of problems is demonstrated, and a methodology for characterizing the surface in the local region using a low-order polynomial is developed.
tracking-