Problem statement: The most important character within optimization problem is the uncertainty of the future returns. Approach: To handle such problems, we utilized probabilistic methods alongside with optimization techniques. We developed single stage and two stage stochastic programming with recourse. The models were developed for risk adverse investors and the objective of the stochastic pro...

In a recent paper [10], an algorithmic approach was presented for the robust (minmax regret) absolute deviation location problem on networks with vertex weights which are linear functions of an uncertain or dynamically changing parameter. In this paper, we present algorithmic and analytical improvements that significantly reduce the computational complexity bounds for the algorithm.

Optimization with a balancing objective often appear in practical problems where humans are implied in the solution. For example, in tasks assignment problems it is a desirable property that the workload is fairly distributed among the workers. In general, a violation measure of the perfect balance can be defined as the Lp norm of the vector of variables minus their mean. Two global constraints...

Lot-streaming is the process of splitting a job (lot) into a number of smaller sublots so that successive operations can be overlapped in a multi-stage production system. This paper presents a procedure for minimizing the mean weighted absolute deviation from due dates when jobs are scheduled in a lot-streaming #ow shop. This performance criterion has been shown to be non-regular and requires a...

Traditionally, classical Markowitz’s model has been usually employed to approach with the portfolio optimization. However, this model, contrary to its theoretical reputation, is scarcely used to construct a large-scale portfolio, due to its unrealistic assumption and tremendous computational complexity associated with solving a large-scale quadratic programming problem. In this paper, a mean-ab...

This paper addresses the minimization of the mean absolute deviation from a common due date in a two-machine flowshop scheduling problem. Initially, a job scheduling algorithm that obtains an optimal schedule for a given job sequence is presented. This algorithm is used with a job insertion procedure to generate a group of heuristics that differ on the initial job sequencing rule. Computational...