Allocation of computing resources is a crucial issue when dealing with a huge number of tasks to be completed according to a given deadline and cost constraints. The task scheduling to several resources (e.g. grid, cloud or a supercomputer) with different characteristics is not trivial, especially if a trade-off in terms of time and cost is considered. We propose an allocation approach able to fulfill the given requirements about time and cost through the use of optimizing techniques and an adaptive behavior. Simulated productions of tasks have been run in order to evaluate the characteristics of the proposed approach.