Today, directional sensor networks (DSNs) have received a great deal of attention. A DSN is composed of several self-configurable directional sensors with adjustable spherical sectors of limited angles, which can provide coverage on several targets distributed randomly within a defined area. One of the most significant problems associated with this type of networks, which has been already proved as an NP-hard problem, is monitoring the maximum number of targets by means of minimum number of sensors. Another aspect of the problem is how to extend the lifetime of such networks concerning the limited power source of the sensors. An appropriate solution to this problem is the use of scheduling technique in environments with densely-distributed sensors. In this paper, we proposed an imperialist competitive-based scheduling algorithm capable of providing near-optimal coverage through determining the priority of the targets that can be monitored by fewer sensors. To evaluate the proposed algorithm performance, the obtained results were compared to those of a target-oriented greedy-based algorithm already proposed in the literature. The final results showed the acceptable competency of the proposed algorithm in terms of solving the problem in hand.