Pervasive systems help access to multimedia documents at any time, from anywhere and through several devices (smart TV, laptop, tablet, etc.). Nevertheless, due to changes in users’ contexts (e.g. noisy environment, preferred language, public place, etc.), restrictions on correct access to these documents may be imposed. One possible solution is to adapt their contents using adaptation services so that they comply, as far as possible, with the current constraints. In this respect, several adaptation approaches have been proposed. However, when it comes to selecting the required adaptation services, they often carry out this task according to predefined configurations or deterministic algorithms. Actually, the efficient selection of adaptation services is one of the key-elements involved in improving the quality of service in adaptation processes. To deal with this issue (i.e. the efficient selection of adaptation services), we first provide an enriched problem formulation as well as methods that we use in problem-solving. Then, we involve standard and compact evolutionary algorithms to find efficient adaptation plans. The standard version is usually adopted in systems that are not subject to specific constraints. The compact one is used in systems for which constraints on computational resources and execution time are considered. The proposal is validated through simulation, experiments and comparisons according to performance, execution time and energy consumption. The obtained results are satisfactory and encouraging.