AbstractAs finite state models to represent a discrete optimization problem given in the form of an r-ddp (recursive discrete decision process), three subclasses of r-msdp (recursive monotone sequential decision process) are introduced in this paper. They all have a feature that the functional equations of dynamic programming hold and there exists an algorithm (in the sense of the theory of computation) to obtain the set of optimal policies. (In this sense, we may call them solvable classes of discrete dynamic programming.) Besides the algorithms for obtaining optimal policies, two types of representations are extensively studied for each class of r-msdp's. Other related decision problems are also discussed. It turns out that some of them a...
We propose a general branch-and-bound algorithm for discrete optimization in which binary decision d...
Dynamic programming (DP) is one of the most important mathematical programming methods. However, a m...
AbstractWe obtain the dynamic programming equations for discrete Goursat systems, we prove that they...
AbstractAs finite state models to represent a discrete optimization problem given in the form of an ...
In the earlier papers by Karp and Held and by Ibaraki, the representation of a discrete optimization...
It is known that various discrete optimization problems can be represented by finite state models ca...
In conjunction with the problem of transforming a given optimization problem into a form from which ...
AbstractA finite state sequential decision process (sdp) is a model which is able to represent a wid...
Many sequential decision problems can be formulated as Markov decision processes (MDPs) where the op...
To unify and generalize the branch-and-bound method used in operations research and the heuristic se...
Dynamic programming is a mathematical technique for solving certain types of sequential decision pro...
Value-function approximation is investigated for the solution via Dynamic Programming (DP) of contin...
Dynamic Programming is a recursive method for solving sequential decision problems (hereafter abbrev...
Dynamic Programming (DP) is a popular tool to solve combinatorial problems. This paradigm is ubiquit...
We develop a formal model of enumeration problems and define dynamic programming in its setting. Dyn...
We propose a general branch-and-bound algorithm for discrete optimization in which binary decision d...
Dynamic programming (DP) is one of the most important mathematical programming methods. However, a m...
AbstractWe obtain the dynamic programming equations for discrete Goursat systems, we prove that they...
AbstractAs finite state models to represent a discrete optimization problem given in the form of an ...
In the earlier papers by Karp and Held and by Ibaraki, the representation of a discrete optimization...
It is known that various discrete optimization problems can be represented by finite state models ca...
In conjunction with the problem of transforming a given optimization problem into a form from which ...
AbstractA finite state sequential decision process (sdp) is a model which is able to represent a wid...
Many sequential decision problems can be formulated as Markov decision processes (MDPs) where the op...
To unify and generalize the branch-and-bound method used in operations research and the heuristic se...
Dynamic programming is a mathematical technique for solving certain types of sequential decision pro...
Value-function approximation is investigated for the solution via Dynamic Programming (DP) of contin...
Dynamic Programming is a recursive method for solving sequential decision problems (hereafter abbrev...
Dynamic Programming (DP) is a popular tool to solve combinatorial problems. This paradigm is ubiquit...
We develop a formal model of enumeration problems and define dynamic programming in its setting. Dyn...
We propose a general branch-and-bound algorithm for discrete optimization in which binary decision d...
Dynamic programming (DP) is one of the most important mathematical programming methods. However, a m...
AbstractWe obtain the dynamic programming equations for discrete Goursat systems, we prove that they...