Abstract
• Integrating product segmentation and customer choice into service network design. • Endogenous delivery quantities and flexible time restrictions. • Parallel genetic algorithm with custom large neighborhood search. • Integrated, profit-maximizing model outperforms sequential optimization. • Adding shorter due times proves to be a profitable strategy. Express parcel carriers offer a wide range of guaranteed delivery times in order to separate customers who value quick delivery from those that are less time but more price sensitive. To reflect the additional complexity this segmentation adds to the task of optimizing the logistics operations, we present a new model that accounts for the interplay between pricing of due times, customer decisions and the associated restrictions in the distribution process. This profit-maximizing express shipment service network design problem is solved by a heuristic solution approach that simultaneously determines the ideal set of offered delivery times, the associated pricing scheme and the load plan in order to maximize profit. High-quality solutions for realistically-sized instances are derived by a genetic-algorithm-based heuristic that exploits information of previously evaluated iterations. Using this new integrated approach, we provide insight on the potential benefit of an integrated model over sequential optimization of revenue and delivery cost. We also investigate the impact of tighter delivery due times on resource requirements and whether more granular service segmentation can be considered a profitable strategy in multimodal express parcel delivery networks.
Highlights
Driven by a booming e-commerce sector, express parcel carriers have experienced rapid growth in transportation volumes
That we have introduced the two basic components of our model we can combine them in order to derive an integrated, profit maximizing approach, referred to as integrated express shipment service network design problem (IESSNDP)
We implemented our heuristic Asynchronous Evolution with Route Pattern Exchanges (AE-route-pattern exchange (RPE)) with MATLAB R2017a
Summary
Driven by a booming e-commerce sector, express parcel carriers have experienced rapid growth in transportation volumes. As the network size of an integrated express parcel carrier is typically large, the main focus of these papers is on managing the complexity of the associated space-time graph These efforts eventually culminate in the works of Armacost, Barnhart, and Ware (2002), who introduce the so-called composite variable formulation of ESSND. This idea is later complemented by a column generation procedure in Louwerse, Mijnarends, Meuffels, Huisman, and Fleuren (2014) and extended by flexible hubassignments in Quesada-Pérez, Lange, and Tancrez (2018) While these formulations allow for realistically-sized multimodal express networks, the lack of explicit flow variables greatly limits the possibilities to enforce flexible delivery time requirements or similar path-based restrictions which are key to implementing RMcomponents
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