Multiple alternative options are frequently available for the protection, maintenance or restoration of conservation areas. The choice of a particular management action can have large effects on the species occurring in the area, because different actions have different effects on different species. Together with the fact that conservation funds are limited and particular management actions are costly, it would be desirable to be able to identify where, and what kind of management should be applied to maximize conservation benefits. Currently available site-selection algorithms can identify the optimal set of sites for a reserve network. However, these algorithms have not been designed to answer what kind of action would be most beneficial at these sites when multiple alternative actions are available. We describe an algorithm capable of solving multi-species planning problems with multiple management options per site. The algorithm is based on benefit functions, which translate the effect of a management action on species representation levels into a value, in order to identify the most beneficial option. We test the performance of this algorithm with simulated data for different types of benefit functions and show that the algorithm’s solutions are optimal, or very near globally optimal, partially depending on the type of benefit function used. The good performance of the proposed algorithm suggests that it could be profitably used for large multi-action multi-species conservation planning problems.