Degeneracy: Resolve or Avoid?
讨论了两种用于线性规划的投影梯度算法，一种通过Wolfe方法解决退化问题，另一种通过求解带约束的最小二乘问题避免退化，并在随机生成的问题上比较了它们的性能。
Two projected gradient algorithms for linear programming are discussed. The first uses a conventional enough steepest edge approach, and implements a version of Wolfe's method for resolving any problems of degeneracy. The second makes use of a steepest descent direction which is calculated by solving a linear least squares problem subject to bound constraints, and avoids problems of degeneracy altogether. They are compared using randomly generated problems which permit the specification of (known) degenerate minima. The results appear to favour the more conventional method as problem sizes get larger.