In this paper, we introduce a new city logistics problem arising in the last mile distribution of e-commerce. The problem involves two levels of routing problems. The first requires a design of the routes for a vehicle fleet located at the depots to transport the customer demands to a subset of the satellites. The second level concerns the routing of a vehicle fleet from the satellites to serve all of the customers. A feature of the problem is that customers may provide different delivery options, allowing them to pick up their packages at intermediate pickup facilities. The objective is to minimize the total distribution cost. To solve the problem, a hybrid multi-population genetic algorithm is proposed. An effective heuristic algorithm is designed to generate initial solutions, and several procedures are designed to better manage the population as well as exploit and explore the solution space. The proposed method is tested on a large family of instances, including a real-world instance; the computational results obtained show the effectiveness of the different components of the algorithm.
Zhou, L., Baldacci, R., Vigo, D., Wang, X.u. (2018). A Multi-Depot Two-Echelon Vehicle Routing Problem with Delivery Options Arising in the Last Mile Distribution. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 265(2), 765-778 [10.1016/j.ejor.2017.08.011].
A Multi-Depot Two-Echelon Vehicle Routing Problem with Delivery Options Arising in the Last Mile Distribution
Baldacci, Roberto
;Vigo, Daniele;
2018
Abstract
In this paper, we introduce a new city logistics problem arising in the last mile distribution of e-commerce. The problem involves two levels of routing problems. The first requires a design of the routes for a vehicle fleet located at the depots to transport the customer demands to a subset of the satellites. The second level concerns the routing of a vehicle fleet from the satellites to serve all of the customers. A feature of the problem is that customers may provide different delivery options, allowing them to pick up their packages at intermediate pickup facilities. The objective is to minimize the total distribution cost. To solve the problem, a hybrid multi-population genetic algorithm is proposed. An effective heuristic algorithm is designed to generate initial solutions, and several procedures are designed to better manage the population as well as exploit and explore the solution space. The proposed method is tested on a large family of instances, including a real-world instance; the computational results obtained show the effectiveness of the different components of the algorithm.File | Dimensione | Formato | |
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