In a general class of discrete optimization problems with min-sum objective function, some of the elements may have random costs associated with them. In such a situation, the notion of optimality needs to be suitably modified. We define an optimal solution to be a feasible solution with the...

Given a set of elements, each having a profit and cost associated with it, and a budget, the 0-1 knapsack problem finds a subset of the elements with maximum possible combined profit subject to the combined cost not exceeding the budget. In this paper we study a stochastic version of the problem...

In this paper we introduce a concept of skewness and suggest its measure among a class of unimodal distributions. The measure is built on the lack of symmetry of the density function around the the mode of the distribution. It is shown to satisfy all standard properties expected from a measure...

In this paper we consider stochastic discrete optimization problems (DOP) in which feasible solutions remain feasible irrespective of the randomness of the problem parameters. We introduce the concept of the risk associated with a solution and define optimal solution in terms of having least...