Abstract
The problem of searching the extremum of a scalar function of a vector argument is considered. It is assumed that a finite set of algorithms, each of which is capable of finding the extremum, is specified. Every algorithm is characterized by a given number of operators each of which is identified with the state of the system. Each algorithm is defined by a transition probability matrix over the possible states (operators) and a corresponding matrix of the respective changes in the value of the function toward the extremal point.
A procedure is given for selecting an optimal sequence of algorithms which maximizes the total expected change in the value of the function toward the optimum.
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References
Rastrigin, L. A.,Statistical Search Methods (in Russian), Nauka, Moscow, USSR, 1968.
Bellman, R.,Dynamic Programming, Princeton University Press, Princeton, New Jersey, 1957.
Howard, R. A.,Dynamic Programming and Markov Processes, MIT Press, Cambridge, Massachusetts, 1960.
Nemhauser, Y. L.,Introduction to Dynamic Programming, John Wiley and Sons, New York, New York, 1967.
Dech, G.,Guide to Practical Application of Laplace Transform (in Russian), Nauka, Moscow, USSR, 1965.
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Communicated by R. A. Howard
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Rubinstein, Y. Choice of optimal search strategy. J Optim Theory Appl 18, 309–317 (1976). https://doi.org/10.1007/BF00933814
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DOI: https://doi.org/10.1007/BF00933814