Summary: Traditional supermarket chains that are adopting an omni-channel approach must now carry out the order picking and delivery processes to serve online orders, previously done by the customer. The complexity of the logistics processes has increased, therefore modelling and optimising e-grocery operations becomes definitely important. Since there are few studies modelling order picking and delivery processes, we propose an approach that simultaneously optimises the decision variables of different functions which have traditionally been treated separately. In this study, we present a linear programming model for store-based e-fulfilment strategies with multiple picking locations. The proposed model optimises the allocation of online orders to stores, based on the e-fulfilment costs. As well as minimising the picking and delivery costs, the proposed approach consolidates workloads in order to avoid idle times and reduce the amount of resources required. A weighted sum method is applied to compute the solution, integrating parameters that represent different store features such as the product range, sales mode and physical store activities. The proposed model has been tested on one of the largest grocery sellers, showing that substantial savings can be achieved by reallocating orders to different stores, time windows and delivery vehicles. By focusing on optimising e-fulfilment resources, this approach serves as a guide for traditional grocery sellers to redesign their supply chains and to facilitate decision-making at a managerial level.