Benders decomposition [1] is a solving strategy based on the separation of the variables of the problem. It is often introduced as a basis for models and techniques using the complementary strengths of constraint programming and optimization techniques. Hybridization schemes have appeared recently and provided interesting computational results [4, 5, 7, 8]. They have been extended [2, 3, 6] to ...

We present a cooperation technique using an accurate management of nogoods to solve a hard real-time problem which consists in assigning periodic tasks to processors in the context of fixed priorities preemptive scheduling. The problem is to be solved off-line and our solving strategy is related to the logic based Benders decomposition. A master problem is solved using constraint programming wh...

The Magnanti–Wong method – accelerating Benders decomposition – is shown to exhibit difficulties due to its dependence on the subproblem; an independent version is therefore introduced. The method additionally requires a – sometimes intractable – master problem core point; for several applications it is proved and experimentally verified that alternative points may be used. c © 2008 Elsevier B....

Given a graph with nonnegative edge weights and node pairs Q, we study the problem of constructing a minimum weight set of edges so that the induced subgraph contains at least K edge-disjoint paths containing at most L edges between each pair in Q. Using the layered representation introduced by Gouveia (1998), we present a formulation for the problem valid for any K, L ! 1. We use a Benders dec...

One of the most challenging issues in multi-objective problems is finding Pareto optimal points. This paper describes an algorithm based on Benders Decomposition Algorithm (BDA) which tries to find Pareto solutions. For this aim, a multi-objective facility location allocation model is proposed. In this case, an integrated BDA and epsilon constraint method are proposed and it is shown that how P...

Novel Optimality Cuts for Two-Stage Stochastic Mixed-Integer Programs The applicability and use of two-stage stochastic mixed-integer programs is well-established, thus calling efficient decomposition algorithms to solve them. Such typically rely on optimality cuts approximate the expected second stage cost function from below. In “A Converging Benders’ Decomposition Algorithm Recourse Models,”...

In this paper, a two-stage robust optimisation is presented for an uncapacitated hub location problem in which demand uncertain and the level of conservatism controlled by uncertainty budget. first stage, locations establishing facilities were determined, allocation decisions made second stage. An accelerated Benders decomposition algorithm was used to solve problem. Computational experiments s...