Planning of Truck Platooning for Road-Network Capacitated Vehicle Routing Problem
Yilang Hao, Zhibin Chen, Xiaotong Sun, Lu Tong
TL;DR
The paper tackles planning truck platooning within a road-network capacitated VRP with time windows, integrating vehicle dispatch, energy costs, and platooning benefits. It formulates a MILP (RCVRPTW-TP-R) that captures routing, scheduling, weight effects, and platoon interactions on a road graph, and linearizes nonlinear cost terms for tractability. A 3-stage solution—grouping via Knapsack DP, route construction with a Modified Insertion heuristic, and schedule-focused optimization with route-then-schedule iterations and a dynamic link-cost update—delivers high-quality solutions efficiently. Numerical experiments on a toy network and the Yangtze River Delta network demonstrate platooning gains, competitive performance against CPLEX, and rich sensitivity analyses showing how factors like fuel rate, dispatch cost, platoon size, capacity, and time-window tolerance shape costs and savings. The work offers practical insights for operators considering platooning in real-world, multi-demand logistics and suggests avenues for extending the model with goods transfer and enhanced optimization strategies.
Abstract
Truck platooning, a linking technology of trucks on the highway, has gained enormous attention in recent years due to its benefits in energy and operation cost savings. However, most existing studies on truck platooning limit their focus on scenarios in which each truck can serve only one customer demand and is thus with a specified origin-destination pair, so only routing and time schedules are considered. Nevertheless, in real-world logistics, each truck may need to serve multiple customers located at different places, and the operator has to determine not only the routing and time schedules of each truck but also the set of customers allocated to each truck and their sequence to visit. This is well known as a capacitated vehicle routing problem with time windows (CVRPTW), and considering the application of truck platooning in such a problem entails new modeling frameworks and tailored solution algorithms. In light of this, this study makes the first attempt to optimize the truck platooning plan for a road-network CVRPTW to minimize the total operation cost, including vehicles' fixed dispatch cost and energy cost, while fulfilling all delivery demands within their time window constraints. Specifically, the operation plan will dictate the number of trucks to be dispatched, the set of customers, and the routing and time schedules for each truck. In addition, the modeling framework is constructed based on a road network instead of a traditional customer node graph to better resemble and facilitate the platooning operation. A 3-stage algorithm embedded with a "route-then-schedule" scheme, dynamic programming, and modified insertion heuristic, is developed to solve the proposed model in a timely manner. Numerical experiments are conducted to validate the modeling framework, demonstrate the performance of the proposed solution algorithm, and quantify the benefit of truck platooning.