A malleable task is a computational unit which may be executed on any arbitrary number of processors whose execution time depends on the amount of resources alloted to is. This paper presents a new approach for scheduling a set of independent malleable tasks which leads to a worst case guarantee of 3/2+epsilon for the minimization of the parallel execution time, for any fixed epsilon>0. The main idea of this approach is to focus on the determination of a good allotment, then, to solve the resulting problem with a fixed number of processors by a simple scheduling algorithm. The first phase is based on a dual approximation technique where the allotment problem is expressed as a knapsack problem for partitionning the set of tasks into two shelves of respective height 1 and 1/2.