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Linear and Dynamic Programming in Markov Chains *
Author(s) -
Kislev Yoav,
Amiad Amotz
Publication year - 1968
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.2307/1237875
Subject(s) - dynamic programming , linear programming , markov chain , cover (algebra) , maximization , mathematical optimization , computer science , simplex algorithm , simplex , bellman equation , function (biology) , value (mathematics) , mathematics , combinatorics , engineering , mechanical engineering , machine learning , evolutionary biology , biology
Some essential elements of the Markov chain theory are reviewed, along with programming of economic models which incorporate Markovian matrices and whose objective function is the maximization of the present value of an infinite stream of income. The linear programming solution to these models is presented and compared to the dynamic programming solution. Several properties of the solution are analyzed and it is shown that the elements of the simplex tableau contain information relevant to the understanding of the programmed system. It is also shown that the model can be extended to cover, among other elements, multiprocess enterprises and the realistic cases of programming in the face of probable deterioration of the productive capacity of the system or its total destruction.