1. A computerized design and process scheduling optimization method, comprising the steps of: building a CPM schedule of a project; mapping, during a planning stage of said project, pattern sets of cut-off dates of said project to said CPM schedule; identifying, during said planning stage, project cut-off date weeks corresponding to the pattern sets of the project cut-off dates; applying said pattern sets and corresponding project cut-off date weeks as inputs to a neural network pattern recognition model; using at least one of the generated patterns to train the neural network pattern recognition model to classify work planned at specified cut-off dates; using the remaining patterns to test the neural network pattern recognition model after it has been trained; monitoring the project, during the construction stage of said project, at said same cut-off dates; preparing, at any desired cut-off date, a corresponding descriptive pattern, said corresponding descriptive pattern describing actual work accomplishments during a time period defined by said any desired cut-off date; inputting said descriptive pattern to said neural network pattern recognition model which, responsively, declares a week of convergence that said descriptive pattern input tends to converge; and comparing said week of convergence declared by said neural network pattern recognition model to said cut-off date week of said associated cut-off date pattern set thereby indicating whether actual progress of the project is on schedule, ahead of schedule, or behind schedule.