Optimization of Stochastic Response Surfaces Subject to Constraints with Linear Programming

Abstract

This research investigated an alternative to the traditional approaches of optimizing a stochastic response surface subject to constraints. This research investigated the bias in the expected value of the solution, possible alternative decision variable settings, and a method to improve the solution. A three step process is presented to evaluate stochastic response surfaces subject to constraints. Step 1 is to use a traditional approach to estimate the response surface and a covariance matrix through regression. Step 2 samples the objective function of the linear program (i.e., response surface) and identifies the extreme points visited. Step 3 presents a method to estimate the optimal extreme point and present that information to a decision maker.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1992
Accession Number
ADA248108

Entities

People

  • Robert G. Harvey

Organizations

  • Air Force Institute of Technology

Tags

DTIC Thesaurus Topics

  • Air Force
  • Applied Mathematics
  • Computer Programming
  • Computer Programs
  • Covariance
  • Data Science
  • Experimental Design
  • Information Science
  • Linear Programming
  • Literature Surveys
  • Mathematical Programming
  • Monte Carlo Method
  • Operations Research
  • Optimization
  • Random Variables
  • Statistics
  • Test And Evaluation

Readers

  • Computational Modeling and Simulation
  • Operations Research
  • Statistical inference.