A CHANCE-CONSTRAINED MODEL FOR REAL-TIME CONTROL IN RESEARCH AND DEVELOPMENT MANAGEMENT

Abstract

Funding of research projects is considered as encompassing three stages: (1) an initial short run plan for funding based upon projected regular demands and availability subject to random deviations; (2) adjustment of the initial plan to take into account the actual regular demands and availability and the funding of significant break-throughs which occur at random intervals preempting other demands; and (3) a plan for longer-run availability and demands which constitute a 'posture' desired subsequent to the funding adjustments of (2). The essence of the distribution of the unexpected demands is multimodality with low probability of occurrence but high resource demand when they do occur. This approach represents a substantial departure from the usual planning model development which produces only an optimal plan based on forecasted developments without provision for adjustment when the forecasted events actually materialize and additional unexpected demands are placed on resources. The adjustment process explored here--which provides the mechanism for optimal implementation of the original plan or control of resource allocation--enables optimal response to information received in 'real-time' avoiding the frequently observed over- or under- response to receipt of such information without reference to the impact of the interim decision on future capabilities.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1965
Accession Number
AD0621512

Entities

People

  • Abraham Charnes
  • Andrew C. Stedry

Organizations

  • Northwestern University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Availability
  • Computer Programming
  • Computers
  • Convex Programming
  • Distribution Functions
  • Emergencies
  • Engineering
  • Linear Programming
  • Military Research
  • New York
  • Normal Distribution
  • Probability
  • Productivity
  • Random Variables
  • Research Management
  • United States
  • Universities

Readers

  • Economics
  • Public Financial Management and Budgeting
  • Regression Analysis.