Abstract
This paper presents a new algorithm for the solution of multi-state dynamic programming problems, referred to as the Progressive Optimality Algorithm. It is a method of successive approximation using a general two-stage solution. The algorithm is computationally efficient and has minimal storage requirements. A description of the algorithm is given including a proof of convergence. Performance characteristics for a trial problem are summarized.
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References
R. Bellman,Dynamic programming (Princeton University Press, Princeton, N. J., 1957).
R. Bellman,Adaptive control processes (Princeton University Press, Princeton, N. J., 1961).
G.B. Dantzig, “A control problem of Bellman”,Management Science, 17 (9) 1971, 542–546.
H.R. Howson and N.G.F. Sancho, “A two-stage algorithm for sequential decisions problems”,INFOR II (2) (1973) 163–176.
W.I. Zangwill,Nonlinear programming, a unified approach (Prentice-Hall, Englewood Cliffs, N.J., 1969).
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The authors acknowledge financial assistance received from the National Reserach Council of Canada, grants A8648 and A4051, which partially supported this research.
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Howson, H.R., Sancho, N.G.F. A new algorithm for the solution of multi-state dynamic programming problems. Mathematical Programming 8, 104–116 (1975). https://doi.org/10.1007/BF01580431
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DOI: https://doi.org/10.1007/BF01580431