Service Network Design for Parcel Trucking
Rocco Rocco, Adolfo Antonio
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We develop a large-scale package express service network design methods using integer programming optimization models specified on flat network models that capture important timing constraints to ensure that package flows meet service constraints. In the first part, we focus on shuttle activities and develop optimization technology for the design of shuttle services using novel rate-based models to determine package flow paths as well as vehicle routes. A computational study using data from a large Chinese package company demonstrates that the technology produces a cost-effective service network design for shuttle schedules with excellent on-time performance. The second part presents a strategic hub selection problem developing a cost-effective greedy heuristic approach that solves tractable integer programming models to add a single intermediate hub on each iteration. A computational study shows that the greedy approach selects geographically-distributed and cost-effective hubs for package transfer, and moreover, the heuristic outperforms the full optimization model by a 20% gap difference for the relevant test instances. In the last part, we develop a new approach for solving the flow planning problem of service network design for large-scale networks with timing constraints. We introduce a so-called generalized in-tree, referred to as GIT, which has useful operational benefits. We demonstrate, via a computational study, that imposing a discretized GIT structure that groups remaining times into fixed-width buckets of 2 hours or 4 hours leads to solutions that are only 2% to 4% more costly than those that do not require GIT structure but significantly simpler to operationalize.