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Papers by Daniel Villeneuve

Transportation Science, 2000

The problem considered involves finding the minimum cost path, with cost and time being two indep... more The problem considered involves finding the minimum cost path, with cost and time being two independent quantities that govern the shortest path. In this problem, each arc is associated with a cost of traversing the arc as well as the time required to traverse it and each node is associated with a lower bound and an upper bound on the time of departure from that node. For example, the time at which a parcel can be sent from a FedEx dispatching station depends upon the working hours of the station. In this case the working hours on a particular day provide a lower and upper bound on the departure time at the node. The parcel dropped off at a station also has a certain waiting time before it

European Journal of Operational Research, 2005

We consider a variant of the constrained shortest path problem, where the constraints come from a... more We consider a variant of the constrained shortest path problem, where the constraints come from a set of forbidden paths (arc sequences) that cannot be part of any feasible solution. Two solution approaches are proposed for this variant. The first uses Aho and Corasick's keyword matching algorithm to filter paths produced by a k-shortest paths algorithm. The second generalizes Martins' deviation path approach for the k-shortest paths problem by merging the original graph with a state graph derived from Aho and Corasick's algorithm. Like Martins' approach, the second method amounts to a polynomial reduction of the shortest path problem with forbidden paths to a classic shortest path problem. Its significant advantage over the first approach is that it allows considering forbidden paths in more general shortest path problems such as the shortest path problem with resource constraints. Ó 2004 Published by Elsevier B.V.

Fleet Management and Logistics, 1998

The need for an integrating framework for vehicle routing and crew scheduling

Operations Research, 2005

Column generation is often used to solve problems involving set-partitioning constraints, such as... more Column generation is often used to solve problems involving set-partitioning constraints, such as vehicle-routing and crew-scheduling problems. When these constraints are in large numbers and the columns have on average more than 8-12 nonzero elements, column generation often becomes inefficient because solving the master problem requires very long solution times at each iteration due to high degeneracy. To overcome this difficulty, we introduce a dynamic constraint aggregation method that reduces the number of set-partitioning constraints in the master problem by aggregating some of them according to an equivalence relation. To guarantee optimality, this equivalence relation is updated dynamically throughout the solution process. Tests on the linear relaxation of the simultaneous vehicle and crew-scheduling problem in urban mass transit show that this method significantly reduces the size of the master problem, degeneracy, and solution times, especially for larger problems. In fact, for an instance involving 1,600 set-partitioning constraints, the master problem solution time is reduced by a factor of 8.

Annals of Operations Research, 2005

Column generation has become a powerful tool in solving large scale integer programs. It is well ... more Column generation has become a powerful tool in solving large scale integer programs. It is well known that most of the often reported compatibility issues between pricing subproblem and branching rule disappear when branching decisions are based on imposing constraints on the subproblem's variables. This can be generalized to branching on variables of a socalled compact formulation. We constructively show that such a formulation always exists under mild assumptions. It has a block diagonal structure with identical subproblems, each of which contributes only one column in an integer solution. This construction has an interpretation as reversing a Dantzig-Wolfe decomposition. Our proposal opens the way for the development of branching rules adapted to the subproblem's structure and to the linking constraints.

Discrete Mathematics, 1999

Transportation Science, 1998

Abstract This paper describes the Preferential Bidding Problem solved in the airline industry to ... more Abstract This paper describes the Preferential Bidding Problem solved in the airline industry to construct personalized monthly schedules for pilots and officers. This problem consists in assigning to crew members pairings, days off, annual leaves, training periods, etc., while ...