This contribution presents a discrete particle swarm optimization (DPSO) approach for the multi-level lot-sizing problem (MLLP), which is an uncapacitated lot sizing problem dedicated to materials requirements planning (MRP) systems. The originality of the proposed DPSO approach is that it is based on cost modification. By the way, we use PSO for that it has been developed: the continuous optimization. Each particle of the swarm is represented by a matrix of logistic costs. A sequential approach heuristic, using Wagner-Whitin algorithm, is then used to determine the associated production planning. The first results obtained are very encouraging. Our DPSO outperforms the results recently published with other nature-inspired algorithms.