During recent years, the number and scale of natural disasters have been increasing steadily. In view of this, a crucial aspect of humanitarian logistics is ensuring that relief materials reach the needy in an efficient and quick manner. Crowdsourcing is a concept that has been gaining momentum over the last few years as a highly potential tool for improving disaster response. This paper defines a crowdsourced humanitarian relief vehicle routing problem and proposes a heuristic to generate good quality solutions in reasonable time. The algorithm is based on an Iterated Local Search (ILS) scheme. Extensive computational studies are done on randomly generated instances to gain insights on the performance of the heuristic and on the impact of the problem features on solution quality. In addition, instances mimicking the shape of real cities are generated and results are analyzed.