Value Added Linear Optimization of Resources (VALOR)
Abstract
Each year, the US Army procures billions of dollars worth of weapons and equipment so that its worldwide mission of defense can be accomplished. The process of deciding what equipment to procure, in what quantities, and in what timeframes to best respond to the threat posed by potential adversaries, is extremely complex, requiring extensive analysis. Two techniques commonly used in this analysis are mathematical programming and cost estimation. Although they are related through constraints on available funds for procurement, the use of nonlinear cost learning curves, which more accurately represent system costs as a function of quantity produced, have not been incorporated into the mathematical programming formulations that compute the quantities of items to be procured. As a result, the solutions obtained could be either suboptimal or even in feasible with respect to budgetary limitations. In this paper, we present a mixed integer linear programming formulation that uses a piecewise linear approximation of the learning curve costs for a more accurate portrayal of budgetary constraints, in addition, implementation issues are discussed, and performance results are given.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1992
- Accession Number
- ADA251105
Entities
People
- Andrew G. Loerch
Organizations
- Center for Army Analysis