Investors typically measure an asset’s potential to diversify a portfolio by its correlations with the portfolio’s other assets, but correlation is useful only if it provides a good estimate of how an asset’s returns co-occur cumulatively with the other asset returns over the investor’s...

Dynamic Programming (DP) is a process of deriving an optimal solution to a mathematical problem that has an objective function and environmentally varying limitations. DP has some difficulties to set up structural equations as in other management science techniques. In this context, DP,...

In the classical Harris-Wilson (1915) inventory model all the cost associated with the formula was taken to be constant and which also does not depend on any quantity. There are many practical situations where this is not true. This paper considers an inventory model where the carrying cost...

We propose an alternative approach to stochastic programming based on Monte-Carlo sampling and stochastic gradient optimization. The procedure is by essence probabilistic and the computed solution is a random variable.

In facility layout problems, a major concern is the optimal design or remodeling of the facilities of an organization. The decision maker's objective is to arrange the facility in an optimal way, so that the interaction among functions (i.e. machines, inventories, persons) and places (i.e....

A version of the classical secretary problem is studied, in which one is interested in selecting one of the b best out of a group of n differently ranked persons who are presented one by one in a random order. It is assumed that b is bigger than or equal to 1 is a preassigned number. It is...

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...

The utopia point of a multicriteria optimization problem is the vector that specifies for each criterion the most favourable among the feasible values. The Euclidean compromise solution in multicriteria optimization is a solution concept that assigns to a feasible set the alternative with...