As climate change becomes more crucial, transporting products in urban areas by bicycle gains popularity. More companies start using bicycles as an alternative transportation mode and face challenges to efficiently satisfy the needs of their customers and employees. While designing the bike routes for pick up and delivery, it is required to take into account the energy needed by cyclists to move. The energy consumed in a bike route has to be kept under a certain threshold for cyclists to be able to pedal during the whole work shift. This leads to a new variant of the vehicle routeing problem called the bike routeing problem which aims at tackling constraints arising for bicycle deliveries. We propose a novel Mixed Integer Linear Programming model to determine the bike routes for delivering goods in urban areas. An Evolutionary Local Search algorithm is developed to efficiently solve the problem using new split and local search procedures. Experimental results obtained on random and real instances show the accuracy and stability of the proposed algorithms, as well as the relevance of the new problem.