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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.
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Adel et al. (1984) studied this question.
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