Stochastic analysis of the departure and quasi-input processes in a versatile single-server queue.
Stochastic Behaviour of a Robot-Safety Device System
Stochastic bottleneck transportation problem with flexible supply and demand quantity
We consider the following bottleneck transportation problem with both random and fuzzy factors. There exist supply points with flexible supply quantity and demand points with flexible demand quantity. For each supply-demand point pair, the transportation time is an independent positive random variable according to a normal distribution. Satisfaction degrees about the supply and demand quantity are attached to each supply and each demand point, respectively. They are denoted by membership functions...
Stochastic dynamic programming applied to hydrothermal power systems operation planning based on the convex hull algorithm.
Stochastic dynamic programming with random disturbances
Several peculiarities of stochastic dynamic programming problems where random vectors are observed before the decision ismade at each stage are discussed in the first part of this paper. Surrogate problems are given for such problems with distance properties (for instance, transportation problems) in the second part.
Stochastic geometric programming with an application
In applications of geometric programming, some coefficients and/or exponents may not be precisely known. Stochastic geometric programming can be used to deal with such situations. In this paper, we shall indicate which stochastic programming approaches and which structural and distributional assumptions do not destroy the favorable structure of geometric programs. The already recognized possibilities are extended for a tracking model and stochastic sensitivity analysis is presented in the context...
Stochastic goal programming wth recourse
In this article we discuss several alternative formulations for Stochastic Goal Programming. Only one of these models, which is a particular case of the Stochastic Programs with Recourse, is also compatible with Bayesian Decision Theory. Moreover, it is posible to approximate its solutions by means of an iterative algorithm.
Stochastic Inventory Models Involving Variable Lead Time With a Service Level Constraint
Stochastic optimization problems with second order stochastic dominance constraints via Wasserstein metric
Optimization problems with stochastic dominance constraints are helpful to many real-life applications. We can recall e. g., problems of portfolio selection or problems connected with energy production. The above mentioned constraints are very suitable because they guarantee a solution fulfilling partial order between utility functions in a given subsystem of the utility functions. Especially, considering (where is a system of non decreasing concave nonnegative utility functions) we obtain...
Stochastic performance measurement in two-stage network processes: A data envelopment analysis approach
In classic data envelopment analysis models, two-stage network structures are studied in cases in which the input/output data set are deterministic. In many real applications, however, we face uncertainty. This paper proposes a two-stage network DEA model when the input/output data are stochastic. A stochastic two-stage network DEA model is formulated based on the chance-constrained programming. Linearization techniques and the assumption of single underlying factor of the data are used to construct...
Stochastische dynamische Optimierung als Spezialfall linearer Optimierung in halbgeordneten Vektorräumen.
Stoghastig behavior of an intermittently used system
Strategic staffing model for electric utilities.
Strategické hry. I
Strategické hry. II
Strategies for LP-based solving a general class of scheduling problems.
In this work we describe some strategies that have been proved to be very efficient for solving the following type of scheduling problems: Assume a set of jobs is to be performed along a planning horizon by selecting one from several alternatives for doing so. Besides selecting the alternative for each job, the target consists of choosing the periods at which each component of the work will be done, such that a set of scheduling and technological constraints is satisfied. The problem is formulated...
Stratified filtered sampling in stochastic optimization.
Strict convex regularizations, proximal points and augmented lagrangians
Strict convex regularizations, proximal points and augmented lagrangians
Proximal Point Methods (PPM) can be traced to the pioneer works of Moreau [16], Martinet [14, 15] and Rockafellar [19, 20] who used as regularization function the square of the Euclidean norm. In this work, we study PPM in the context of optimization and we derive a class of such methods which contains Rockafellar's result. We also present a less stringent criterion to the acceptance of an approximate solution to the subproblems that arise in the inner loops of PPM. Moreover, we introduce a new...
Strict minimizers of order in nonsmooth optimization problems
In the paper, some sufficient optimality conditions for strict minima of order in constrained nonlinear mathematical programming problems involving (locally Lipschitz) -convex functions of order are presented. Furthermore, the concept of strict local minimizer of order is also used to state various duality results in the sense of Mond-Weir and in the sense of Wolfe for such nondifferentiable optimization problems.