In this work, we present a Lagrangean relaxation of the hull-reformulation of discrete-continuous optimization problems formulated as linear generalized disjunctive programs (GDP). The proposed Lagrangean relaxation has three important properties. The first property is that it can be applied to any linear GDP. The second property is that the solution to its continuous relaxation always yields 0...

We address the optimal design of a multi-echelon supply chain and the associated inventory systems in the presence of uncertain customer demands. By using the guaranteed service approach to model the multi-echelon stochastic inventory system, we develop an optimization model for simultaneously optimizing the transportation, inventory and network structure of a multi-echelon supply chain. We for...

This work deals with the optimal synthesis of groundwater remediation networks for the valorization of anionic pollutants by means of emulsion pertraction technology using hollow fiber modules (HFM). Superstructures that incorporate all possible design alternatives are proposed. The aim of this work is to obtain a minimum cost groundwater remediation network that allows treatment of groundwater...

Video on demand (VoD) is a technology used to provide a number of programs to a number of users on request. In developing a VoD system, a fundamental problem is load balancing, which is further characterized by optimally placing videos to a number of predefined servers and routing the user program requests to available resources. In this paper, an exact solution algorithm is described to solve ...

We compare heuristics based on Lagrangean and surrogate relaxations of the Maximal Covering Location Problem (MCLP). The Lagrangean relaxation of MCLP used in this paper has the integrality property and the surrogate relaxed problem we solve is the LP relaxation of the original 0ÿ1 knapsack problem. The heuristics were compared using 331 test problems available in the literature, corresponding ...

We present a mixed integer linear programming (MIP) formulation for a traffic engineering problem where we address the restricted number of active tunnels on each link in the presence of diversity requirements. The design has significance in networks such as multi-protocol-label-switching (MPLS)based networks where such conditions can be applicable. For large networks, we present the solution a...

The Traveling Salesman Problem (TSP) is a classical Combinatorial Optimization problem intensively studied. The Lagrangean relaxation was first applied to the TSP in 1970. The Lagrangean relaxation limit approximates what is known today as HK (Held and Karp) bound, a very good bound (less than 1% from optimal) for a large class of symmetric instances. It became a reference bound for new heurist...

-In this paper a Lagrangean decomposition technique for solving the scheduling problem for Hot Charged Rolling (HCR) in the continuous casting process which involves sequencing and grouping. This Lagrangian relaxation algorithm is proposed that incorporate two sets of constraints into the objective function after applying the variable splitting technique. The relaxed problem has a special struc...

In this work we present a global optimization algorithm for solving a class of large-scale nonconvex optimization models that have a decomposable structure. Such models are frequently encountered in two-stage stochastic programming problems, engineering design, and also in planning and scheduling. A generic formulation and reformulation of the decomposable models is given. We propose a speciali...

In this paper, production planning and scheduling problems are addressed through a hierarchical framework. The planning problem aggregates orders in the planning period and considers uncertainty utilizing a multi-stage stochastic programming formulation where three stages are considered with increasing level of uncertainty. The planning model includes material balances and time horizon constrai...