The quality of the delivery service is a crucial asset for an e-grocer to create and maintain a loyal customer-base. With the rapid market growth of e-grocers over the last decade, there is an urgent need for e-grocer specific routing systems. Although stochastic and dynamic routing models are studied for a wide range of applications, e-grocer specific models are missing in the literature. This paper investigates the concept of flexible deliveries, which introduces differentiated time window sizes. This creates the possibility for real-time re-optimization of the sequence of customers in a trip in order to improve the on-time delivery performance. The potential of flexible deliveries is investigated by means of computational experiments in which historic trip instances from the Dutch e-grocer Picnic are used. It is shown that, when re-optimization is activated, on-time delivery performance is improved and this benefit is significant when flexible deliveries represent at least 10% of the deliveries. When 10% of the deliveries are flexible, the number of late deliveries can be reduced by up to 18% and the number of extreme late deliveries (≥15 min late) up to 27%. This improved on-time delivery performance comes at the cost of a maximum of 2% increase in the average time spent per delivery.

This paper proposes a model for charge scheduling of electric vehicles in last-mile distribution that takes into account battery degradation. A mixed integer linear programming formulation is proposed that minimizes labor, battery degradation and time-dependent energy costs. The benefit of implementing charge schedule optimization is assessed for a real-life case study at e-grocer Picnic. It is shown that charging optimization yields an overall reduction of charging costs by 25.2% when compared to the current operational charging performance. Furthermore, the impacts of three different shift schedule types, the increase in vehicle battery size and the coordinated charging are investigated. It turns out that more energy demanding shift schedules result in higher average charging cost per charged amount of energy. The introduction of a larger battery size as well as coordinated charging show potential for decreasing overall costs.