Motivated by a real-world industrial problem, this work deals with the integration of planning and scheduling in the operation of a network of batch plants. The network consists of single-stage, multiproduct batch plants located in different sites, which can exchange intermediate products in order to blend them to obtain finished products. The time horizon is given and divided into multiple tim...

ddsip.vSD is a C-implementation of a number of scenario decomposition algorithms for stochastic linear programs with firstor second-order stochastic dominance constraints induced by mixed-integer linear recourse. The program is based on a previous implementation of scenario decomposition algorithms for mean-risk models of A. Märkert [20]. Main idea of the decomposition algorithms is the Lagrang...

This paper presents a dynamic (or multi-period) hub location problem. It proposes a branch-and-bound algorithm that uses a Lagrangean relaxation to obtain lower and upper bounds at the nodes of the tree. The Lagrangean function exploits the structure of the problem and can be decomposed into smaller subproblems which can be solved efficiently. In addition, some reduction procedures based on the...

This paper presents two Lagrangean relaxation approaches for the NP-hard multiple-depot vehicle scheduling problem in public mass transit and reports on computational investigations. Our Lagrangean relaxation approaches can be applied to generate very tight lower bounds and to compute feasible solutions eeciently. A further application is to use the Lagrangean relaxations as new pricing strateg...

The problem of reconstructing bicolored images from their orthogonal projections is studied. A binary integer programming model is formulated to build small size bicolored images with smoothness properties. Since the problem is NP-complete, we provide an iterative approximation based on lagrangean relaxation. Keyword: Discrete Tomography; Images Reconstruction; Lagrangean Relaxation

This paper proposes a new lower bounding procedure for the Uncapacitated Single Allocation p-Hub Median Problem based on Lagrangean relaxation. For solving the resulting Lagrangean subproblem, the given problem structure is exploited: it can be decomposed into smaller subproblems that can be solved efficiently by combinatorial algorithms. Our computational experiments for some benchmark instanc...

We address a dynamic covering location problem of an Unmanned Aerial Vehicle Base Station (UAV-BS), where the sequence single UAV-BS in wireless communication network is determined to satisfy data demand arising from ground users. This especially relevant context smart grid and disaster relief. The vertical movement ability non-convex functions restrict utilizing classical planar approaches. Th...

In this paper we propose a hybrid algorithm for the set covering problem (SCP), which combines L-class enumeration, genetic algorithm (GA) and Lagrangean heuristic. The lexicographical enumeration of L-classes in the linear relaxation of SCP ensures optimality of the resulting solution. Both heuristics are used for obtaining the initial approximate solution. The linear subproblems in L-class en...

We derive a non–linear supersymmetric σ–model for the transport of light (classical waves) through a disordered medium. We compare this model with the well–established non–linear σ–model for the transport of electrons (Schrödinger waves) and display similarities of and differences between both cases. We show that for weak disorder, both models are equivalent (have the same effective Lagrangean)...