Traditional methods for nature conservation reserve design include scoring and Gap analysis, which are simple and easy to use, but the results of these two methods lack reliability. Geographic Information System (GIS) is another widely used method in designing nature reserves nowadays. This paper focuses on two other methods which have been developed and gained popularity in the past two decades, but not used as widely in China. These two methods are mathematical modeling/programming and computer simulation. Mathematical modeling aims to select an optimal subset from a large set of potential sites to assemble a nature reserve which is expected to protect a set of targeted species while satisfying some specific biological and/or ecological constraints. The problem can be formulated as linear and nonlinear optimization models, and solution methods vary depending on the type of formulation. When formal optimization methods fail to solve these models, due to the model size or degree of nonlinearity, heuristics are employed instead of formal optimization. Heuristic methods are computationally convenient and flexible in finding multiple solutions, but the solutions can be significantly suboptimal; therefore this approach does not ensure an optimal allocation of scarce conservation resources. Formal optimization, on the other hand, provides the best possible solution to the problem. However, solving a reserve selection problem to an exact optimum can be computationally challenging and modelers can easily encounter computation difficulties when the number of variables in the model is large. Computer simulation, the second method reviewed in this paper, is used mainly to evaluate a nature reserve in terms of its functionality, delineate functional areas, and predict the impact of specific circumstances such as spatial attributes or climate change on species' persistence. As the solution methods in computer simulation, generally heuristics are employed and the results are displayed in graphical form or even in animation by integrating the simulation software with other software. Results in such forms may look attractive but cautions should be taken in terms of model selection, parameter valuation, and interpretation of the results. Model validation is generally required in computer simulation and the results of a simulation process should be interpreted from a statistical perspective. Both methods, especially computer simulation, require and benefit from user's judgment, expertise, and especially ecological and biological knowledge. Using linear integer programming to guide optimal allocation of conservation resources is extremely important and valuable in China's nature reserve planning and design process, considering the conflict between conservation and development. In this review, relevant issues and potential new research directions are discussed, including: 1) original data needs to provide a basis on which these design methods can work; 2) some more challenging factors such as dynamics, uncertainty, and particularly spatial coherence of the reserve areas; 3) reevaluation and adjustment of model parameters under the projected climate change scenarios; 4) coordination issues of nature conservation and economic development; 5)communication mechanisms between scholars and decision-makers in applications of these design methods in real world reserve planning and design practices; and 6) participation of experts from multiple disciplines and other concerned parties in the reserve design process.