Dynamic programming approach to time-staged convex programs
This paper describes a dynamic programming-like technique for solving large scale (or at least moderately large scale) convex programs which have a time-staged (i.e., ''staircase'') structure. At the heart of the technique is a method for avoiding ''the curse of dimensionality'' which normally prevents the application of dynamic programming to problems whose time stages contain more than just a small number of variables. Three algorithms are developed: a ''backward'' algorithm, a ''forward'' algorithm, and a ''time-symmetric'' algorithm. The ''backward'' algorithm most closely resembles standard dynamic programming since ''pricing'' information propagates from the future back to the past. A strong connection is shown between these D.P.-like techniques and the ''nested decomposition'' algorithms of Manne and Ho, and Abrahamson and Wittrock, particularly the latter. These nested decomposition algorithms are used to solve ''staircase linear programs'' - a special case of the problem considered in this paper.
- Research Organization:
- Stanford Univ., CA (USA). Systems Optimization Lab.
- DOE Contract Number:
- AT03-76ER72018
- OSTI ID:
- 5725575
- Report Number(s):
- SOL-85-3; ON: DE85010616
- Country of Publication:
- United States
- Language:
- English
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