Solving the Classification Problem in Discriminant Analysis Via Linear and Nonlinear Programming Methods*
证明用非线性规划方法解决判别分析中的分类问题是可行的，是对已有线性规划方法的扩展。蒙特卡洛模拟实验表明新方法有前景，并讨论了其在商业决策中的应用。
ABSTRACT This paper demonstrates the feasibility of applying nonlinear programming methods to solve the classification problem in discriminant analysis. The application represents a useful extension of previously proposed linear programming‐based solutions for discriminant analysis. The analysis of data obtained by conducting a Monte Carlo simulation experiment shows that these new procedures are promising. Future research that should promote application of the proposed methods for solving classification problems in a business decision‐making environment is discussed.