Multiobject spectroscopy is applied in numerous modern astronomical facilities conducting observations of a large number of targets per pointing. Assigning the maximum number of targets to these instruments requires efficient algorithms. We present a simple and effective algorithm, the averaging (Aver) algorithm, to maximize the number of assigned targets for the first few visits of a given field. In comparison to the draining (Dra) algorithm, our algorithm increases the target completeness by 1% to 2% by employing Poisson distributed and real catalogs from the Large Sky Area Multiobject Fiber Spectroscopic Telescope survey. Moreover, our algorithm performs ∼375 times faster than the conventionally applied simulated annealing algorithm and yields a slightly higher completeness. We further optimize the Aver and Dra algorithms by combining the genetic algorithm (GA) and the differential evolution method. The Aver is slightly optimized by this method, whereas the Dra algorithm is improved by 0.9% to 1.6%, suggesting that our proposed Aver algorithm approaches maximum completeness. Furthermore, we find that the GA can optimize the rotation angle with a specially designed fitness function in the case of focal-plane rotation that is expected to be realized in the future, achieving a 1.8% increase in the number of the targets observed. In particular, our Aver algorithm assigns the maximum number of targets within the first few visits.