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...

We propose a novel two-phase bounding and decomposition approach to compute optimal and near-optimal solutions to large-scale mixed-integer investment planning problems that have to consider a large number of operating subproblems, each of which is a convex optimization. Our motivating application is the planning of transmission and generation in which policy constraints are designed to incenti...

The capacitated plant location problem (CPL) consists of locating a set of potential plants with capacities, and assigning a set of customers to these plants. The objective is to minimize the total fixed and shipping costs while at the same time demand of all the customers can be satisfied without violating the capacity restrictions of the plants. The CPL is a well-known combinatorial optimizat...

We report a computational study of two-stage SP models on a large set of benchmark problems and consider the following methods: (i) Solution of the deterministic equivalent problem by the simplex method and an interior point method, (ii) Benders decomposition (L-shaped method with aggregated cuts), (iii) Regularised decomposition of Ruszczyński (Math Program 35:309–333, 1986), (iv) Benders deco...

When solving combinatorial optimization problems it can happen that using a single technique is not efficient enough. In this case, simplifying assumptions can transform a huge and hard to solve problem in a manageable one, but they can widen the gap between the real world and the model. Heuristic approaches can quickly lead to solutions that can be far from optimality. For some problems, that ...

We propose a heuristic adaptation of logic-based Benders decomposition to the home health care problem. The objective is design routes and schedules for health care workers who visit patient homes, so as to minimize cost while meeting all patient needs and work requirements. We solve the Benders master problem by a greedy heuristic that is enhanced by the propagation facilities of constraint pr...

Recent work have exhibited specific structure among combinatorial problem instances that could be used to speed up search or to help users understand the dynamic and static intimate structure of the problem being solved. Several Operations Research approaches apply decomposition or relaxation strategies upon such a structure identified within a given problem. This paper presents how Benders dec...

This paper focuses on solving two-stage stochastic mixed integer programs (SMIPs) with general mixed integer decision variables in both stages. We develop a decomposition algorithm in which the first stage approximation is solved using a branch-and-bound tree with nodes inheriting Benders’ cuts that are valid for their ancestor nodes. In addition, we develop two closely related convexification ...

This paper presents an exact algorithm for the Lock Scheduling Problem (LSP) based on a Combinatorial Benders decomposition. LSP consists of three strongly interconnected sub problems: scheduling the lockages, assigning ships to chambers, and positioning the ships inside the chambers. These three sub problems are interpreted resp. as a scheduling, an assignment, and a packing problem. By combin...

We propose the concept of partial Benders decomposition, based on the idea of retaining a subset of scenario subproblems in the master formulation and develop a theory to support it that illustrates how it may be applied to any stochastic integer program with continuous recourse. Such programs are used to model many practical applications such as the one considered in this paper, network design...