When the cost of reducing the duration of activities is convex and nonlinear, it may be advisable (to reduce the computing burden) to seek a “satisficing” answer, in which the project is compressed to a desired completion time with a prespecified tolerable relative error. We treat the problem of constructing the optimal first degree interpolating linear spline that guarantees such maximal error and consider various possible refinements.