In 1997 two papers_new applying the metaheuristics Tabu Search (TS) and Heuristic Concentration (HC) tothe p-median problem were published in consecutive volumes of the European Journal of OperationalResearch. Here we apply the method of HC some of the data sets which were used for...

In market share analysis, it is well recognized that we have often inadmissible predicted marketshare, which means that some of predictors take the values outside the range [0, 1] and the totalsum of predicted shares is not always one, so called logical inconsistency. In this article, basedon...

Combined forecasts from a linear and a nonlinear model areinvestigated for timeseries with possibly nonlinear characteristics. The forecasts arecombined by aconstant coefficient regression method as well as a time varyingmethod. Thetime varying method allows for a locally (non)linear model....

Contemporary financial stochastic programs typically involve a trade-offbetween return and (downside)-risk. Using stochastic programming we characterize analytically (rather than numerically) the optimal decisions that follow from characteristic single-stage and multi-stage versions of such...

In this paper we compare the predictive abilility of Stochastic Volatility (SV)models to that of volatility forecasts implied by option prices. We develop anSV model with implied volatility as an exogeneous var able in the varianceequation which facilitates the use of statistical tests for...

In this paper we consider optimization problems defined by a quadraticobjective function and a finite number of quadratic inequality constraints.Given that the objective function is bounded over the feasible set, we presenta comprehensive study of the conditions under which the optimal solution...

In this paper we will describe a Multi-Agent System which iscapable of finding a feasible solution of a specially structuredlinear programming problem. Emphasis is given to correctnessissues and termination detection.

We present algorithms to calculate the stability radius of optimal or approximate solutions of binary programming problems with a min-sum or min-max objective function. Our algorithms run in polynomial time if the optimization problem itself is polynomially solvable. We also extend our results...

A necessary condition - the Principle of Fermat-Lagrange - is offered for mixed smooth-convexoptimization problems. This generalizes and unifies most of the known necessary conditions forconcrete finite and infinite dimensional optimization problems of interest. The new idea in comparisonwith...

In this paper we consider properties of the central path and the analytic center of the optimalface in the context of parametric linear programming. We first show that if the right-hand sidevector of a standard linear program is perturbed, then the analytic center of the optimal face isone-side...