We consider eight problems in which we maximize or minimize threshold probabilities in discounted Markov decision processes with bounded reward set. We show that such problems are classified to two equivalence classes and give a relationship between optimal values and optimal policies of...

In this article, the theoretical aspects of union-soft sets by extending the notions of equivalence relations, partition, composition of relations, and function to the framework of union-soft sets are introduced. Further the Cartesian product, the relation between union-soft sets, induced...

The standard Value Iteration (VI) algorithm, referred to as Value Iteration Pre-Jacobi (PJ-VI) algorithm, is the simplest Value Iteration scheme, and the well-known algorithm for solving Markov Decision Processes (MDPs). In the literature, several versions of VI algorithm were developed in order...

In this paper methods of mixing decision rules are investigated and applied to the so-called multiple job type assignment problem with specialized servers which is modeled as continuous time Markov decision process. Performance optimization is difficult for this assignment problem, but...

In this paper we study Markov Decision Process (MDP) problems with the restriction that at decision epochs only a finite number of given Markovian decision rules may be applied. The elements of the finite set of allowed decision rules should be mixed to improve the performance. The set of...

This dissertation develops a new methodology and associated solution tools toachieve optimal operations and maintenance strategies for wind turbines, helpingreduce operational costs and enhance the marketability of wind generation. Theintegrated framework proposed includes two optimization...