We introduce the stochastic linear programming (SLP) model classes, which will be considered in this paper, on the basis of a small-scale linear programming problem. The solutions for the various problem formulations are discussed in a comparative fashion. We point out the need for model and solution analysis. Subsequently, we outline the basic ideas of selected major algorithms for two classes...

Design of a logistics network in proper way provides a proper platform for efficient and effective supply chain management. This paper studies a multi-period, multi echelon and multi-product integrated forward-reverse logistics network under uncertainty. First, an efficient complex mixed-integer linear programming (MILP) model by considering some real-world assumptions is developed for the inte...

In stochastic scheduling, we want to allocate a limited amount of resources to a set of jobs that need to be serviced. Unlike in deterministic scheduling, however, the parameters of the system may be stochastic. For example, the time it takes to process a job may be subject to random fluctuations. Stochastic scheduling problems occur in a variety of practical situations, such as manufacturing, ...

Most of the real-life decision-making problems have more than one conflicting and incommensurable objective functions. In this paper, we present a multiobjective two-stage stochastic linear programming problem considering some parameters of the linear constraints as interval type discrete random variables with known probability distribution. Randomness of the discrete intervals are considered f...

in any supply chain, distribution planning of products is of great importance to managers. with effective and flexible distribution planning, mangers can increase the efficiency of time, place, and delivery utility of whole supply chain. in this paper, inventory routing problem (irp) is applied to distribution planning of perishable products in a supply chain. the studied supply chain is compos...

This paper formulates a stochastic inventory model for a single-period seasonal or fashion product inventory system consisting of multiple stocking echelons in series and retailers. By transforming model, an equivalent two-stage stochastic linear program model is developed to solve this stochastic inventory problem, which makes the inventory problem easier to analyze. The optimal placement poli...

In the context of public transportation system, improving the service quality and robustness through minimizing the average passengers waiting time is a real challenge. This study provides robust stochastic programming models for train timetabling problem in urban rail transit systems. The objective is minimization of the weighted summation of the expected cost of passenger waiting time, its va...

This thesis develops integer linear programming models for and studies the complexity of problems in the areas of maintenance optimization and location–routing. We study how well the polyhedra defined by the linear programming relaxation of the models approximate the convex hull of the integer feasible solutions. Four of the papers consider a series of maintenance decision problems whereas the ...

We consider risk-averse formulations of multistage stochastic linear programs. For these formulations, based on convex combinations of spectral risk measures, risk-averse dynamic programming equations can be written. As a result, the Stochastic Dual Dynamic Programming (SDDP) algorithm can be used to obtain approximations of the corresponding risk-averse recourse functions. This allows us to de...

bilevel linear programming  is a decision making problem with a two-level decentralized organization. the textquotedblleft leadertextquotedblright~ is in the upper level and the textquotedblleft followertextquotedblright, in the lower. making a decision at one level affects that at the other one. in this paper, bilevel linear programming  with inexact parameters has been studied and a method is...