This paper considers the design and analysis of algorithms for vehicle routing and scheduling problems with time window constraints. Given the intrinsic difficulty of this problem class, approximation methods seem to offer the most promise for practical size problems. After describing a variety of heuristics, we conduct an extensive computational study of their performance. The problem set includes routing and scheduling environments that differ in terms of the type of data used to generate the problems, the percentage of customers with time windows, their tightness and positioning, and the scheduling horizon. We found that several heuristics performed well in different problem environments; in particular an insertion-type heuristic consistently gave very good results. A key element of many distribution systems is the Subject classification: 632 heuristic programming, 831 transportation, 483 distance algorithms.

The vehicle routing problem with time windows (VRPTW) is a generalization of the vehicle routing problem where the service of a customer can begin within the time window defined by the earliest and the latest times when the customer will permit the start of service. In this paper, we present the development of a new optimization algorithm for its solution. The LP relaxation of the set partitioning formulation of the VRPTW is solved by column generation. Feasible columns are added as needed by solving a shortest path problem with time windows and capacity constraints using dynamic programming. The LP solution obtained generally provides an excellent lower bound that is used in a branch-and-bound algorithm to solve the integer set partitioning formulation. Our results indicate that this algorithm proved to be successful on a variety of practical sized benchmark VRPTW test problems. The algorithm was capable of optimally solving 100customer problems. This problem size is six times larger than any reported to date by other published research.

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This paper presents the development of new elimination tests which greatly enhance the performance of a relatively well established dynamic programming approach and its application to the minimization of the total traveling cost for the traveling salesman problem with time windows. The tests take advantage of the time window constraints to significantly reduce the state space and the number of state transitions. These reductions are performed both a priori and during the execution of the algorithm. The approach does not experience problems stemming from increasing problem size, wider or overlapping time windows, or an increasing number of states nearly as rapidly as other methods. Our computational results indicate that the algorithm was successful in solving problems with up to 200 nodes and fairly wide time windows. When the density of the nodes in the geographical region was kept constant as the problem size was increased, the algorithm was capable of solving problems with up to 800 nodes. For these problems, the CPU time increased linearly with problem size. These problem sizes are much larger than those of problems previously reported in the literature.

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This paper presents a survey of the research on the Vehicle Routing Problem with Time Windows (VRPTW), an extension of the Capacitated Vehicle Routing Problem. In the VRPTW, the service at each customer must start within an associated time window and the vehicle must remain at the customer location during service. Soft time windows can be violated at a cost while hard time windows do not allow for a vehicle to arrive at a customer after the latest time to begin service. We first present a multi-commodity network flow formulation with time and capacity constraints for the VRPTW. Approximation methods proposed in the literature to derive upper bounds are then reviewed. Then we explain how lower bounds can be obtained using optimal approaches, namely, Lagrangean relaxation and column generation. Next, we provide branching and cutting strategies that can be embedded within these optimal approaches to produce integer solutions. Special cases and extensions to the VRPTW follow as well as our conclusions. Résumé Cet article synthèse porte sur les récents développements concernant le problème du routage de véhicules sous des contraintes de fenêtres de temps. Dans ce problème, le serviceà un client doit débuterà l'intérieur d'un intervalle de temps. Celui-ci peutêtre, soit relaché au prix d'une certaine pénalité, soit rigide, auquel cas, il n'est pas permis de dépasser la limite supérieure. Nous présentons un modèle de réseau multi-flots avec des contraintes de temps et de capacité. Les méthodes heuristiques permettant de calculer des bornes supérieures sont d'abord présentées. Suivent les modèles d'optimisation basés sur la relaxation lagrangienne et la génération de colonnes pourévaluer des bornes inférieures. Enfin, on présente les stratégies de coupes et de branchements liéesà ces méthodes afin de déterminer des solutions entières. L'article se termine par l'étude de cas particuliers et d'extensions ainsi que nos conclusions.

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