The design of multiple experiments is commonly undertaken via suboptimal strategies, such as batch (open-loop) design that omits feedback or greedy (myopic) design that does not account for future effects. This paper introduces new strategies for the optimal design of sequential experiments. First, we rigorously formulate the general sequential optimal experimental design (sOED) problem as a dy...

This paper develops a maintenance strategy for repairable products that combines imperfect maintenance actions at pre-scheduled times and minimal repair actions for failures. Under a power law process of failures, an expected total cost is developed that involves the sum of the total cost of imperfect preventive maintenances and the expected total cost of minimal repairs. Moreover, a searching ...

We are interested in solving large-scale Markov Decision Problems. The classical method of Dynamic Programming provides a mathematical framework for nding optimal solutions for a given Markov Decision Problem. However, for Dynamic Programming algorithms become computationally infeasible when the underlying Markov Decision Problem evolves over a large state space. In recent years, a new methodol...

In this paper, convex semi-infinite programming is converted to an optimal control model of neural networks and the optimal control model is solved by iterative dynamic programming method. In final, numerical examples are provided for illustration of the purposed method.

We consider the role of dynamic programming in sequential learning problems. These problems require deciding which information to collect in order to best support later actions. Such problems are ubiquitous, appearing in simulation, global optimization, revenue management, and many other areas. Dynamic programming offers a coherent framework for understanding and solving Bayesian formulations o...

Locally repairable codes, or locally recoverable codes (LRC for short) are designed for application in distributed and cloud storage systems. Similar to classical block codes, there is an important bound called the Singleton-type bound for locally repairable codes. In this paper, an optimal locally repairable code refers to a block code achieving this Singleton-type bound. Like classical MDS co...

In this paper, we consider sequential dynamic team decision problems with nonclassical information structures. First, address the problem from point of view a “manager” who seeks to derive optimal strategy in centralized process. We structural results that yield an state for which does not depend on control strategy, and thus it can lead programming decomposition where optimizatio...

Semi-Markov Decision Problems are continuous time generalizations of discrete time Markov Decision Problems. A number of reinforcement learning algorithms have been developed recently for the solution of Markov Decision Problems, based on the ideas of asynchronous dynamic programming and stochastic approximation. Among these are TD(,x), Q-Iearning, and Real-time Dynamic Programming. After revie...

Dynamic optimization problems, including optimal control problems, have typically relied on the solution techniques of dynamic programming, involving the sequential solution of certain optimality equations. However, many problems cannot be handled this way, due to complex constraints, a continuous state space, and other complicating factors. When recast as mathematical programs relying on the p...