Nowadays, reaching a high level of employee satisfaction in efficient schedules is an important and difficult task faced by companies. We tackle new variant the personnel scheduling problem under unknown demand considering via endogenous uncertainty depending on combination their preferred received schedules. address this context reserve staff scheduling, unstudied operational from transit indu...

In this paper we present a framework for solving stochastic programs with complete integer recourse and discretely distributed right-hand side vector, using Gröbner basis methods from computational algebra to solve the numerous second-stage integer programs. Using structural properties of the expected integer recourse function, we prove that under mild conditions an optimal solution is containe...

We study several joint facility location and inventory management problems with stochastic retailer demand. In particular, we consider cases with uncapacitated facilities, capacitated facilities, correlated retailer demand, stochastic lead times, and multicommodities. We show how to formulate these problems as conic quadratic mixed-integer problems. Valid inequalities, including extended polyma...

We consider stochastic programming problems with probabilistic constraints in volving random variables with discrete distributions They can be reformulated as large scale mixed integer programming problems with knapsack constraints Using speci c properties of stochastic programming problems and bounds on the prob ability of the union of events we develop new inequalities for these mixed integer...

In this article, the design of a Supply Chain Network (SCN) consisting of several suppliers, production plants, distribution centers and retailers, is considered. Demands of retailers are considered stochastic parameters, so we generate amounts of data via simulation to extract a few demand scenarios. Then a mixed integer two-stage programming model is developed to optimize simultaneously two o...

Stochastic integer programs (SIP) represent a very difficult class of optimization problems arising from the presence of both uncertainty and discreteness in planning and decision problems. Although applications of SIP are abundant, nothing is available in the way of computational software. On the other hand, commercial software packages for solving deterministic integer programs have been arou...

We synergistically apply queueing theory, integer programming, and stochastic simulation to determine an optimal staffing policy for a repair call handling center. A stationary Markovian queueing model is employed to determine minimal staffing levels for a sequence of time intervals with varying call volumes and mean handling times. These staffing requirements populate an integer programmodel f...

This paper presents an investigation on the computational complexity of stochastic optimization problems. We discuss a scenariobased model which captures the important classes of two-stage stochastic combinatorial optimization, two-stage stochastic linear programming, and two-stage stochastic integer linear programming. This model can also be used to handle chance constraints, which are used in...

resource limitation in zero time may cause to some profitable projects not to be selected in project selection problem, thus simultaneous project portfolio selection and scheduling problem has received significant attention. in this study, budget, investment costs and earnings are considered to be stochastic. the objectives are maximizing net present values of selected projects and minimizing v...