This paper addresses a class of two-stage robust optimization models with integer adversarial variables. We discuss the importance of this class of problems in modeling two-stage robust resource planning problems where some tasks have uncertain arrival times and duration periods. We apply Dantzig-Wolfe decomposition to exploit the structure of these models and show that the original problem red...

In this paper, a new model is proposed for the integrated logistics network designing problem. In many research papers in this area, it is assumed that there is only one option for the capacity of each facility in the network. However, this is not a realistic assumption because generally there may be many possible options for the capacity of the facility that is being established. Usually the c...

We address the balancing problem of transfer lines in this paper to find the optimal line balancing that minimizes the nonproductive time. We focus on the tool change time and face orientation change time both of which influence the makespane. We consider machine capacity limitations and technological constraints associated with the manufacturing process of auto cylinder heads. The problem is r...

In this paper we explore the possibility of applying the notions of Recoverable Robustness and Price of Recoverability (introduced by [5]) to railway rolling stock planning, being interested in recoverability measures that can be computed in practice, thereby evaluating the robustness of rolling stock schedules. In order to lower bound the Price of Recoverability for any set of recovery algorit...

We adopt Benders’ decomposition algorithm to solve scenariobased Stochastic Constraint Programs (SCPs) with linear recourse. Rather than attempting to solve SCPs via a monolithic model, we show that one can iteratively solve a collection of smaller sub-problems and arrive at a solution to the entire problem. In this approach, decision variables corresponding to the initial stage and linear reco...

We present the mean value cross decomposition algorithm and its simple enhancement for the two-stage stochastic linear programming problem with complete recourse. The mean value cross decomposition algorithm employs the Benders (primal) subproblems as in the so-called “L-shaped” method but eliminates the Benders master problem for generating the next trial first-stage solution, relying instead ...

We adopt Benders’ decomposition algorithm to solve scenariobased Stochastic Constraint Programs (SCPs) with linear recourse. Rather than attempting to solve SCPs via a monolithic model, we show that one can iteratively solve a collection of smaller sub-problems and arrive at a solution to the entire problem. In this approach, decision variables corresponding to the initial stage and linear reco...

Many real problems can bemodelled as robust shortest path problems on digraphs with interval costs, where intervals represent uncertainty about real costs and a robust path is not too far from the shortest path for each possible configuration of the arc costs. In this paper we discuss the application of a Benders decomposition approach to this problem. Computational results confirm the efficien...

in today’s competitive business environment, the design and management of supply chainnetwork is one of the most important challenges that managers encounter. the supply chain network shouldbe designed for satisfying of customer demands as well as minizing the total system costs. this paper presentsa multi-period multi-stage supply chain network design problem under demand uncertainty. the prob...

Network problems concern the selection of arcs in a graph in order to satisfy, at minimum cost, some flow requirements, usually expressed in the form of node–node pair demands. Benders decomposition methods, based on the idea of partitioning of the initial problem to two sub-problems and on the generation of cuts, have been successfully applied to many of these problems. This paper presents a n...