Material requirements planning (MRP), in its original form, utilises deterministic lead-time. However, the lead-time uncertainty is a fact of life in most of production systems. Therefore, developing MRP to deal with lead-time uncertainty is of great importance to academics and practitioners. In this paper, the problem of supply planning is considered in a multi-period, multi-level assembly system in which each sub-level has several components whose lead-times are uncertain. A two-objective mathematical model is presented not only to provide the appropriate number of periods in POQ policy, but also to determine the planning lead-time of each sub-level component. The aim of the model is to minimise the expected total cost, and to maximise the customer service level. Furthermore, two metaheuristic algorithms, namely non-dominated sorting genetic algorithm-II (NSGA-II), and multi-objective particle swarm optimisation (MOPSO) are proposed to solve the model. Finally, numerical experiments are carried out to compare the effectiveness of the procedures.