Optimization of Recurrent Stochastic Capacity Expansion Models and Generalization to a Non-Recurrent Model.

Abstract

The determination of optimal expansion sizes X*(K)+1, for recurrent capacity expansion strategies of the form (X,K) where X+1 represents the expansion size undertaken whenever excess demand reaches the value K+1 is considered here, for fixed values K. A POlicy Improvement algorithm is derived to determine optimal expansion sizes for general expansion functions. For a certain class of expansion functions, which includes discrete convex functions, it is shown that the expected discounted costs are unimodal in the expansion size and that the optimal expansion size X*(K)+1 increases monotonically with K; an Interval-Bisection algorithm is given to determine X*(K) for this case. The monotonicity of the optimal expansion size is also demonstrated, prior to integer-truncation, for important classes of concave expansion functions which are continuiously differentiable; a simple Function Iteration algorithm is derived to determine optimal expansion size for this case.

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Document Details

Document Type
Technical Report
Publication Date
Oct 11, 1976
Accession Number
ADA033429

Entities

People

  • R. Scott Shipley

Organizations

  • Stanford University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Determinants (Mathematics)
  • Dynamic Programming
  • Equations
  • Exponential Functions
  • Inequalities
  • Intervals
  • Iterations
  • Linear Systems
  • Military Research
  • Operations Research
  • Optimization
  • Probability
  • Theorems
  • Time Intervals
  • United States

Fields of Study

  • Mathematics

Readers

  • Analytical Mechanics
  • Calculus or Mathematical Analysis
  • Operations Research