Two-Echelon Vehicle-Routing Problem: Optimization of Autonomous Delivery Vehicle-Assisted E-Grocery Distribution

Abstract

The last mile problem of E-grocery Distribution comprises one of the most costly and highest polluting components of the supply chain in which companies deliver goods to end customers. To reduce transport cost and fuel emissions, a new element of ground-based delivery services, autonomous delivery vehicles (ADVs), is included in the E-grocery distribution system for improving delivery efficiency. Thus, the objective of this study is to optimize a two-echelon distribution network for efficient E-grocery delivery, where conventional vans serve the delivery in the first echelon and ADVs serve delivery in the second echelon. The problem is formulated as a two-echelon vehicle routing problem with mixed vehicles (2E-VRP-MV) with a nonlinear objective function, in which the total transport and emission costs are optimized. This optimization is based on the flow assignment at each echelon and to realize routing choice for both the van and ADV. A two-step clustering-based hybrid Genetic Algorithm and Particle Swarm Optimization (C-GA-PSO) algorithm is proposed to solve the problem. First, the end customers are clustered to the intermediate depots, named satellites, based on the minimized distance and maximized demand. To enhance the efficiency of resolving the 2E-VRP-MV-model, a hybrid GA-PSO algorithm is adopted to solve the vehicle routing problem. Computational results of up to 21, 32, 50, and 100 customers show the effectiveness of the methods developed here. At last, the impacts of the layout of the depot-customer and customer density on the total cost are analyzed. This study sheds light on the tactical planning of the multi-echelon sustainable E-grocery delivery network.

New Mobility-Assist E-Grocery Delivery Network: a Load-Dependent Two-Echelon Vehicle Routing Problem With Mixed Vehicles

“…First, customers were assigned to the micro hubs based on the distance and loads of the customers. The clustered nodes were then assigned vehicles and routes were constructed by connecting the nodes ( 18 ).…”

“…2E-VRP was initially proposed by Gonzalez-Feliu ( 16 ), and their newly published outcomes in Perboli et al ( 17 ) showed that 2E-VRP can be used to model delivery system involving a micro hub. The 2E-VRP is attributed to a VRP of two-echelon delivery connected by micro hubs ( 18 ) with unitary mode vehicles or mixed vehicles. For example, vans and cargo bikes ( 19 ), cargo bikes, and parcel lockers ( 20 ) are integrated into a two-echelon system to achieve a sustainable delivery.…”

Two-Echelon Location-Routing Problem with Time Windows and Transportation Resource Sharing

“…Zamar et al [59] studied the bale collection optimization and designed a nearest neighbor approach together with a constrained k-means clustering to achieve the minimization of the fuel consumption and travel time simultaneously. Liu et al [60] proposed a two-step clustering-based hybrid algorithm to solve the two-echelon VRP with mixed vehicles and substantially minimized the transport cost and fuel emissions of the logistics network. Gao et al [61] developed a hybrid algorithm composed of k-means clustering and ant colony algorithm and introduced k-means clustering for handling the location allocation.…”

Multidepot Recycling Vehicle Routing Problem with Resource Sharing and Time Window Assignment

“…Fan et al [44] introduced a clustering algorithm based on the temporal-spatial distance to reduce the computational complexity and enhance the quality of initial solution in MDVRPTW. Liu et al [45] investigated the clustering algorithm that groups customers in terms of the minimum distance and maximum demand to improve the efficiency of solving MDVRPTW.…”