The species composition, abundance and distribution of ichthyoplankton and their changes are important indicators for the investigation of fishery resources. The abundance of ichthyoplankton affects the early supplement and population dynamics of fishery population. Therefore, carrying out necessary scientific surveys is necessary to understand the species diversity of ichthyoplankton in the central and Southern Yellow Sea. Generally, the larger the sample size is, the closer the survey results are to the true values. Considering the time and cost of the survey, balancing the sample size and data quality is needed to achieve the highest accuracy under a certain sample size. The optimal survey design requires that under certain survey demand and cost conditions, the bias and accuracy of the survey objectives are the highest, and the investigation benefit is maximized. Optimization of the sampling design to obtain accurate and reliable survey data with limited survey cost is important in fisheries-independent surveys. In this study the estimate of species richness of ichthyoplankton was the sampling objective. Based on the ichthyoplankton survey data collected in August (summer), October (autumn) 2014, February (winter) and may (spring) 2015 in the coastal waters in central and Southern Yellow Sea, the effect of different sampling designs on estimation of ichthyoplankton species richness was compared using the computer simulation study. In this study, it is assumed that the original survey data can be used as the “true value” reflecting the species composition and species number of fish plankton in the sea area. This paper mainly compares the effects of different sampling designs on the estimation of ichthyoplankton species richness; when the cost is fixed, the sampling design which can achieve a certain species richness detection rate and has small relative estimation error and relative deviation is selected as the optimal sampling design. The results showed that the detection rate of ichthyoplankton species richness increased gradually with the increase of sampling frequency and the number of sampling stations, and the relative estimation error (REE) and relative bias (RB) of the estimate of ichthyoplankton species richness decreased gradually. Stratified random sampling performed better than simple random sampling, and the design effect (D_e) of stratified random sampling with 4 times a year is 0.766. Under different sampling frequencies, the optimal season combinations were spring, spring-summer, spring-summer-autumn and four seasons, and the corresponding REE and RB values were the lowest among different seasonal combinations with the same frequency, and the species richness detection rates were the highest. If the detection rate of species richness was set at 90%, the optimal number of stations was 80 and 60 for stratified random sampling with 3 and 4 times a year, respectively. The sampling method and optimal season combination under different frequencies were optimized under the premise of ensuring the estimation accuracy and precision, which will provide reference for the further optimization of sampling design for ichthyoplankton survey.