Due to recent environmental regulations concerning the release of volatile organic compounds (VOCs), a virtual army of testing personnel has been assigned the task of detecting and repairing faulty equipment leaks. In this work, we develop a strategy for the cost-effective allocation of these testing personnel. The proposed scheme finds a grounding in the probabilistic theory of reliability analysis and culminates with the formulation of a Mixed Integer Linear Programming (MILP) optimization problem. The goal of this optimization problem is to find a testing schedule that achieves minimum cost while maintaining a bound on the expected number of leaks. The formulation is general enough to capture time-varying failure characteristics (i.e. equipment age), quality/cost variations inherent to different testing methods as well as personnel availability considerations. Finally, the algorithm can be applied in a feedback framework to incorporate recent information (such as test results and maintenance actions) into an updated testing schedule. (C) 2003 Elsevier Ltd. All rights reserved.