Eduardo Uchoa

Robust Branch-and-Cut-and-Price for the Capacitated Vehicle Routing Problem

The best exact algorithms for the Capacitated Vehicle Routing Problem (CVRP) have been based on either branch-and-cut or Lagrangean relaxation/column generation. This paper presents an algorithm that combines both approaches: it works over the intersection of two polytopes, one associated with a traditional Lagrangean relaxation over q-routes, the other defined by bound, degree and capacity constraints. This is equivalent to a linear program with exponentially many variables and constraints that can lead to lower bounds that are superior to those given by previous methods. The resulting branch-and-cut-and-price algorithm can solve to optimality all instances from the literature with up to 135 vertices. This more than doubles the size of the instances that can be consistently solved.

A Hybrid GRASP with Perturbations for the Steiner Problem in Graphs

We propose and describe a hybrid GRASP with weight perturbations and adaptive path-relinking heuristic (HGP + PR) for the Steiner problem in graphs. In this multi-start approach, the greedy randomized construction phase of a GRASP is replaced by the use of several construction heuristics with a weight perturbation strategy that combines intensification and diversification elements, as in a strategic oscillation approach. The improvement phase circularly explores two different local search strategies. The first uses anode-based neighborhood for local search, while the second uses a key-path-based neighborhood. An adaptive path-relinking technique is applied to a set of elite solutions as apost-optimization strategy. Computational results on a broad set of benchmark problems illustrate the effectiveness and the robustness of our heuristic, which is very competitive when compared to other approximate algorithms.

Solving capacitated arc routing problems using a transformation to the CVRP

A well-known transformation by Pearn, Assad and Golden reduces a capacitated arc routing problem (CARP) into an equivalent capacitated vehicle routing problem (CVRP). However, that transformation is regarded as unpractical, since an original instance with r required edges is turned into a CVRP over a complete graph with 3r + 1 vertices. We propose a similar transformation that reduces this graph to 2r + 1 vertices, with the additional restriction that a previously known set of r pairwise disconnected edges must belong to every solution. Using a recent branch-and-cut-and-price algorithm for the CVRP, we observed that it yields an effective way of attacking the CARP, being significantly better than the exact methods created specifically for that problem. Computational experiments obtained improved lower bounds for almost all open instances from the literature. Several such instances could be solved to optimality.Scope and purpose The scope of this paper is transforming arc routing problems into node routing problems. The paper shows that this approach can be effective and, in particular, that the original instances may generate node routing instances that behave as if the size is not increased. This result is obtained by slightly modifying the well-known transformation by Pearn, Assad and Golden from capacitated arc routing problem (CARP) to the capacitated vehicle routing problem (CVRP), that is regarded as unpractical. The paper provides a computational experience using a recent branch-and-cut-and-price algorithm for the CVRP. The results are significantly better than the exact methods created specifically for that problem, improving lower bounds for almost all open instances from the literature. Several such instances could be solved to optimality.

A hybrid algorithm for a class of vehicle routing problems

Abstract In this work we propose a hybrid algorithm for a class of Vehicle Routing Problems with homogeneous fleet. A sequence of Set Partitioning (SP) models, with columns corresponding to routes found by a metaheuristic approach, are solved, not necessarily to optimality, using a Mixed Integer Programming (MIP) solver, that may interact with the metaheuristic during its execution. Moreover, we developed a reactive mechanism that dynamically controls the dimension of the SP models when dealing with large size instances. The algorithm was extensively tested on benchmark instances of the following Vechicle Routing Problem (VRP) variants: (i) Capacitated VRP; (ii) Asymmetric VRP; (iii) Open VRP; (iv) VRP with Simultaneous Pickup and Delivery; (v) VRP with Mixed Pickup and Delivery; (vi) Multi-depot VRP; (vii) Multi-depot VRP with Mixed Pickup and Delivery. The results obtained were quite competitive with those found by heuristics devoted to specific variants. A number of new best solutions were obtained.

A hybrid algorithm for the Heterogeneous Fleet Vehicle Routing Problem

This paper deals with the Heterogeneous Fleet Vehicle Routing Problem (HFVRP). The HFVRP generalizes the classical Capacitated Vehicle Routing Problem by considering the existence of different vehicle types, with distinct capacities and costs. The objective is to determine the best fleet composition as well as the set of routes that minimize the total costs. The proposed hybrid algorithm is composed by an Iterated Local Search (ILS) based heuristic and a Set Partitioning (SP) formulation. The SP model is solved by means of a Mixed Integer Programming solver that interactively calls the ILS heuristic during its execution. The developed algorithm was tested in benchmark instances with up to 360 customers. The results obtained are quite competitive with those found in the literature and new improved solutions are reported.

Modeling hop-constrained and diameter-constrained minimum spanning tree problems as Steiner tree problems over layered graphs

The hop-constrained minimum spanning tree problem (HMSTP) is an 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 appropriate layered graph. We prove that the directed cut model for the STP defined in the layered graph, dominates the best previously known models for the HMSTP. We also show that the Steiner directed cuts in the extended layered graph space can be viewed as being a stronger version of some previously known HMSTP cuts in the original design space. Moreover, we show that these strengthened cuts can be combined and projected into new families of cuts, including facet defining ones, in the original design space. We also adapt the proposed approach to the diameter-constrained minimum spanning tree problem (DMSTP). Computational results with a branch-and-cut algorithm show that the proposed method is significantly better than previously known methods on both problems.

Strong bounds with cut and column generation for class-teacher timetabling

This work presents an integer programming formulation for a variant of the Class-Teacher Timetabling problem, which considers the satisfaction of teacher preferences and also the proper distribution of lessons throughout the week. The formulation contains a very large number of variables and is enhanced by cuts. Therefore, a cut and column generation algorithm to solve its linear relaxation is provided. The lower bounds obtained are very good, allowing us to prove the optimality of previously known solutions in three formerly open instances.

Robust branch-cut-and-price for the Capacitated Minimum Spanning Tree problem over a large extended formulation

This paper presents a robust branch-cut-and-price algorithm for the Capacitated Minimum Spanning Tree Problem (CMST). The variables are associated to q-arbs, a structure that arises from a relaxation of the capacitated prize-collecting arborescence problem in order to make it solvable in pseudo-polynomial time. Traditional inequalities over the arc formulation, like Capacity Cuts, are also used. Moreover, a novel feature is introduced in such kind of algorithms: powerful new cuts expressed over a very large set of variables are added, without increasing the complexity of the pricing subproblem or the size of the LPs that are actually solved. Computational results on benchmark instances from the OR-Library show very significant improvements over previous algorithms. Several open instances could be solved to optimality.

Branch-and-cut with lazy separation for the vehicle routing problem with simultaneous pickup and delivery

Abstract We propose a branch-and-cut algorithm for the VRPSPD where the constraints that ensure that the capacities are not exceeded in the middle of a route are applied in a lazy fashion. The algorithm was tested in 87 instances with 50–200 customers, finding improved lower bounds and several new optimal solutions.

Dual Heuristics on the Exact Solution of Large Steiner Problems

Abstract Abstract We present dual heuristics for the directed cut formulation of the Steiner problem in graphs. These heuristics usually give tight lower and upper bounds, and are enough to quickly solve two thirds of the instances from the literature. For harder instances, we propose two exact algorithms using those heuristics: branch-and-ascent, an implicit enumeration without LP solving; and a branch-and-cut that starts from bases provided by dual heuristics, which may be called afterwards to improve convergence. These algorithms have a good practical performance and solved several open instances, including the 1320 series and very large and degenerated problems from VLSI layout.