The Hop-Constrained Minimum Spanning Tree Problem (HMSTP) is a NP-hard problem arising in the design of centralized telecommunication networks with quality of service constraints. We show that the HMSTP is equivalent to a Steiner Tree Problem (STP) in an adequate layered graph. We prove that the directed cut formulation for the STP defined in the layered graph, dominates (in terms of the linear programming relaxation) the best previously known formulations for the HMSTP. We then show how cuts in the extended layered graph space can be projected into new families of cuts in the original design space. We also adapt the proposed approach for the Diameter-Constrained Minimum Spanning Tree Problem (DMSTP). For situations when the diameter is odd we propose a new transformation into a single center problem that is quite effective. Computational results with a branch-and-cut algorithm show that the proposed method is significantly better than previously known methods on both problems.

We present exact algorithms for solving the minimum connected dominating set problem in an undirected graph. The algorithms are based on two approaches: a Benders decomposition algorithm and a branch-and-cut method. We also develop a hybrid algorithm that combines these two approaches. Two variants of each of the three resulting algorithms are considered: a stand-alone version and an iterative probing variant. The latter variant is based on a simple property of the problem, which states that if no connected dominating set of a given cardinality exists, then there are no connected dominating sets of lower cardinality. We present computational results on a large set of instances from the literature.

In this paper, we present a bilevel programming formulation for the problem of strategic bidding under uncertainty in a wholesale energy market (WEM), where the economic remuneration of each generator depends on the ability of its own management to submit price and quantity bids. The leader of the bilevel problem consists of one among a group of competing generators and the follower is the electric system operator. The capability of the agent represented by the leader to affect the market price is considered by the model. We propose two solution approaches for this non-convex problem. The first one is a heuristic procedure whose efficiency is confirmed through comparisons with the optimal solutions for some instances of the problem. These optimal solutions are obtained by the second approach proposed, which consists of a mixed integer reformulation of the bilevel model. The heuristic proposed is also compared to standard solvers for nonlinearly constrained optimization problems. The application of the procedures is illustrated in case studies with configurations derived from the Brazilian power system.

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Given a graph G = (V, E), the maximum leaf spanning tree problem (MLSTP) is to find a spanning tree of G with as many leaves as possible. The problem is easy to solve when G is complete. However, for the general case, when the graph is sparse, it is proven to be NP-hard. In this paper, two reformulations are proposed for the problem. The first one is a reinforced directed graph version of a formulation found in the literature. The second recasts the problem as a Steiner arborescence problem over an associated directed graph. Branch-and-Cut algorithms are implemented for these two reformulations. Additionally, we also implemented an improved version of a MLSTP Branch-and-Bound algorithm, suggested in the literature. All of these algorithms benefit from pre-processing tests and a heuristic suggested in this paper. Computational comparisons between the three algorithms indicate that the one associated with the first reformulation is the overall best. It was shown to be faster than 123 290 A. Lucena et al. the other two algorithms and is capable of solving much larger MLSTP instances than previously attempted in the literature.

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The hop‐constrained survivable network design problem consists of finding a minimum cost subgraph containing K edge‐disjoint paths with length at most H joining each pair of vertices in a given demand set. When all demands have a common vertex, the instance is said to be rooted. We propose a new extended formulation for the rooted case, called hop‐level multicommodity flow (MCF), that can be significantly stronger than the previously known formulations, at the expense of having a larger number of variables and constraints, growing linearly with the number of edges and demands and quadratically with H. However, for the particular case where H = 2, it can be specialized into a very compact and efficient formulation. Even when H = 3, hop‐level‐MCF can still be quite efficient and it has solved several instances from the literature for the first time. © 2012 Wiley Periodicals, Inc. NETWORKS, 2013

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