Benders decomposition has been widely used for solving network design problems. In this paper, we use a branch-and-cut algorithm to improve the separation procedure of Gabrel et al. and Knippel et al. for capacitated network design. We detail experiments on bilayer networks, comparing with Knippel’s previous results.

The design of resilient supply chains under the risk of disruptions at candidate locations for distribution centers (DCs) is formulated as a two-stage stochastic program. The problem involves selecting DC locations, determining storage capacities for multiple commodities, and establishing the distribution strategy in scenarios that describe disruptions at potential DCs. The objective is to mini...

This paper presents an optimization model and its application to a generation expansion planning problem. The proposed model has a generalized network structure and is exploited effectively by Benders’ decomposition algorithm, where a master problem generates trial expansion plans and a set of subproblems compute production cost and system reliability for the trial plan. The applicability of ou...

We consider two-stage stochastic programming problems with integer recourse. The L-shaped method of stochastic linear programming is generalized to these problems by using generalized Benders decomposition. Nonlinear feasibility and optimality cuts are determined via general duality theory and can be generated when the second stage problem is solved by standard techniques. Finite convergence of...

Benders decomposition uses a strategy of “learning from one’s mistakes.” The aim of this paper is to extend this strategy to a much larger class of problems. The key is to generalize the linear programming dual used in the classical method to an “inference dual.” Solution of the inference dual takes the form of a logical deduction that yields Benders cuts. The dual is therefore very different f...

We present an algorithmic approach for solving two-stage stochastic mixed 0-1 problems. The first stage constraints of the Deterministic Equivalent Model have 0–1 variables and continuous variables. The approach uses the Twin Node Family (TNF) concept within the algorithmic framework so-called Branch-and-Fix Coordination for satisfying the nonanticipativity constraints, jointly with a Benders D...

In this paper, two Benders decomposition algorithms and a novel two-stage integer programming-based heuristic are presented to optimize the beam angle and fluence map in Intensity Modulated Radiation Therapy (IMRT) planning. Benders decomposition is first implemented in the traditional manner by iteratively solving the restricted master problem and then identifying and adding the violated Bende...

An airline’s operational disruptions can lead to flight delays that in turn impact passengers, not only through the delays themselves but also through possible missed connections. Since the length of a delay is often not known in advance, we consider preemptive rerouting of airline passengers before the length of the delay is realized. Our goal is to reaccommodate passengers proactively as soon...

We study an unrelated parallel machines scheduling problem with sequence and machine dependent setup times. A logicbased Benders decomposition approach is proposed to minimize the makespan. The decomposition approach is a hybrid model that makes use of a mixed integer programming master problem and a travelling salesman problem subproblem. The master problem is a relaxation of the problem and i...