The introduction of 2-truck platooning ? two trucks virtually coupled driving at less than 1 second headway - will introduce new logistics concepts in the Supply Chain. Carriers obtain fuel consumption reductions through platooning and even higher benefits if they form 2-truck platoons with other carriers. Shippers may encourage their carriers to form as many platoons as possible to exploit the synergy potential, and benefit from lower emissions and more sustainable transport services. This proposal addresses the industrial challenge to be able to schedule platoons or dynamically form platoons on-the-fly, by realizing a collaborative matching and planning competency. This competency builds on Vehicle Routing Problem solutions adding 2-truck platoon planning characteristics and parameters. To that end, we develop a quantitative Platooning-Optimizer (PLATO) that enables the planning and formation of scheduled and dynamic truck platoons. Platoons will be formed within one supply chain network, across multiple networks, and by means of a neutral intermediary Platooning Service Provider (similar to a 4C). Real world data from port-related container transportation and supply chain operations will be used to provide a proof of concept. The collaborative planning has to be evaluated in light of the impact on the supply chain, from financial, strategic, and operations perspectives. Hence, platooning will only become successful if the crucial stakeholders in the supply chain have a positive business case with regards to platooning. To that end, we develop a generic platooning business case build on 2 scenarios for platooning formation: centralised scheduled and on-the-fly ad-hoc matching.

The continuous growth of online sales together with the inefficiency of the last-mile of the e-commerce supply chain puts a lot of pressure on urban areas in terms of congestion, emissions and pollution. It is critical to increase the efficiency of the last-mile deliveries to enhance the financial and environmental performance of internet retailers. The primary goal of this project is to develop and evaluate decision support models and tools to facilitate the optimal design of different delivery service models in online retailing and to identify service models and corresponding operating strategies that provide most benefits in terms of various sustainability criteria. To create more sustainable last-mile operations, the proposed research is organized around two PhD projects, one that particularly focuses on optimizing the delivery operations and one that focuses on the optimal design of the distribution network.