Exact and heuristic solution of the consistent vehicle-routing problem

Providing consistent service by satisfying customer demands with the same driver (driver consistency) at approximately the same time (arrival-time consistency) allows companies in last-mile distribution to stand out among competitors. The consistent vehicle-routing problem (ConVRP) is a multiday problem addressing such consistency requirements along with traditional constraints on vehicle capacity and route duration. The literature offers several heuristics but no exact method for this problem. The state-of-the-art exact technique to solve VRPs-column generation (CG) applied to route-based formulations in which columns are generated via dynamic programming-cannot be successfully extended to the ConVRP because the linear relaxation of route-based formulations is weak. We propose the first exact method for the ConVRP, which can solve medium-sized instances with five days and 30 customers. The method solves, via CG, a formulation in which each variable represents the set of routes assigned to a vehicle over the planning horizon. As an upper bounding procedure, we develop a large neighborhood search (LNS) featuring a repair procedure specifically designed to improve the arrival-time consistency of solutions. Used as stand-alone heuristic, the LNS is able to significantly improve the solution quality on benchmark instances from the literature compared with state-of-the-art heuristics

Service Consistency in Vehicle Routing

This thesis studies service consistency in the context of multi-period vehicle routing problems (VRP) in which customers require repeatable services over a planning horizon of multiple days. Two types of service consistency are considered, namely, driver consistency and time consistency. Driver consistency refers to using the fewest number of different drivers to perform all of the visits required by a customer over a planning horizon and time consistency refers to visiting a customer at roughly the same time on each day he/she needs service. First, the multi-objective consistent VRP is defined to explore the trade-offs between the objectives of travel cost minimization and service consistency maximization. An improved multi-objective optimization algorithm is proposed and the impact of improving service consistency on travel cost is evaluated on various benchmark instances taken from the literature to facilitate managerial decision making. Second, service consistency is introduced for the first time in the literature to the periodic vehicle routing problem (PVRP). In the PVRP, customers may require multiple visits over a planning horizon, and these visits must occur according to an allowable service pattern. A service pattern specifies the days on which the visits required by a customer are allowed to occur. A feasible service pattern must be determined for each customer before vehicle routes can be optimized on each day. Various multi-objective optimization approaches are implemented to evaluate their comparative competitiveness in solving this problem and to evaluate the impact of improving service consistency on the total travel cost. Third, a branch-and-price algorithm is developed to solve the consistent vehicle routing problem in which service consistency is enforced as a hard constraint. In this problem, the objective is to minimize the total travel cost. New constraints are devised to enhance the original mixed integer formulation of the problem. The improved formulation outperforms the original formulation regarding CPLEX solution times on all benchmark instances taken from the literature. The proposed branch-and-price algorithm is shown to be able to solve instances with more than fourteen customers more efficiently than either the existing mixed integer formulation or the one we propose in this paper

Strategic Time Slot Management: A Priori Routing for Online Grocery Retailing

Time slot management refers to the design and control of the delivery time slots offered to customers during the online ordering process. Strategic time slot management is an innovative variant in which only a single time slot is offered each day of the week and a priori delivery routes are used to guide time slot availability. Strategic time slot management simplifies time slot control and fulfillment center operations. We propose a 2-stage stochastic programming formulation for the design of a priori delivery routes and time slot assignments and a sample average approximation algorithm for its solution. An efficient dynamic program is developed for calculating the expected revenue of an a priori route. An extensive computational study demonstrate the efficacy of the proposed approach and provides insights in to the benefits of strategic time slot management

Strategic Time Slot Management: A Priori Routing for Online Grocery Retailing

Time slot management refers to the design and control of the delivery time slots offered to customers during the online ordering process. Strategic time slot management is an innovative variant in which only a single time slot is offered each day of the week and a priori delivery routes are used to guide time slot availability. Strategic time slot management simplifies time slot control and fulfillment center operations. We propose a 2-stage stochastic programming formulation for the design of a priori delivery routes and time slot assignments and a sample average approximation algorithm for its solution. An efficient dynamic program is developed for calculating the expected revenue of an a priori route. An extensive computational study demonstrate the efficacy of the proposed approach and provides insights in to the benefits of strategic time slot management