We develop and test an integrated forecasting and stochastic programming approach to workforce management in call centers. We first demonstrate that parametric forecasts can be used to drive stochastic programs whose results are stable with relatively small numbers of scenarios. We then extend our approach to include forecast updates and two-stage stochastic programs with recourse and provide a...

The purpose of this paper is to present a framework for optimal stochastic power control in interference limited fading wireless channels. The framework is based on applying stochastic programming methods to optimal transmit power allocation. Numerical examples based on applying interior point algorithms to the optimal power control problem are discussed. Furthermore, an application of the stoc...

Fuzzy systems can provide us with universal approximation models of deterministic input–output relationships, but in the stochastic environment few achievements related to the subject have so far achieved. In the paper a novel stochastic Takagi–Sugeno (T–S) fuzzy system is introduced to represent approximately existing randomness in many real-world systems. By recapitulating the general archite...

In this note, we present the necessary mathematical framework for stochastic MPEC models, including some new results on the existence of solutions and on convexity and diierentiability of the implicit upper-level objective function. In so doing, we clarify the links between these models and two-stage stochastic programs with recourse.

This paper presents a paired-vehicle recourse strategy for the vehicle routing problem with stochastic demands (VRPSD). In the VRPSD, a fleet of homogeneous capacitated vehicles is dispatched from a terminal to serve single-period customer demands which are known in distribution when planning but only revealed with certainty upon vehicle arrival. While most existing research for this problem fo...

A large number of problems in production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncertainty. Uncertainty, for instance, governs the prices of fuels, the availability of electricity, and the demand for chemicals. A key difficulty in optimization under uncertainty is in dealing with an uncertainty space ...

In this paper, we study recourse-based stochastic nonlinear programs and make two sets of contributions. The first set assumes general probability spaces and provides a deeper understanding of feasibility and recourse in stochastic nonlinear programs. A sufficient condition, for equality between the sets of feasible first-stage decisions arising from two different interpretations of almost sure...

Considering first-order stochastic dominance constraints for random variables arising as optimal values of stochastic programs with linear recourse, verifiable sufficient conditions for metric regularity are presented. A growth condition developed in [22] has a crucial role in the analysis of the present paper. Implications regarding stability and sensitivity of optimal values and optimal solut...

Using Greedy Clustering Method to Solve Capacitated Location-Routing Problem with Fuzzy Demands Abstract In this paper, the capacitated location routing problem with fuzzy demands (CLRP_FD) is considered. In CLRP_FD, facility location problem (FLP) and vehicle routing problem (VRP) are observed simultaneously. Indeed the vehicles and the depots have a predefined capacity to serve the customerst...