The Distributed Constraint Optimization Problem (DCOP) is able to model many problems in multiagent systems but existing research has not considered the issue of unreliable communication which often arises in real world applications. Limited bandwidth, interference, loss of line-of-sight are some reasons why communication fails in the real world. In this paper we show that an existing asynchronous algorithm for DCOP can be made to operate effectively in the face of message loss through the introduction of a very simple timeout mechanism for selective communication. Despite its simplicity, this mechanism is shown to dramatically reduce communication overhead while preventing deadlocks that can occur when messages are lost. Results show that the optimal solution can be guaranteed even in the presence of message loss and that algorithm performance measured in terms of time to solution degrades gracefully as message loss probability increases.