Abstract
This paper describes solution techniques for scheduling a set of independent jobs on a single machine where the objective is to minimize the mean squared deviation of the completion times about a common due date. A branch and bound algorithm is proposed and implemented using a recursive scheme. The algorithm is tested on job sets drawn from six different distributions of processing times. Computational experiments which compare this approach with the existing methodology indicate that the former is significantly faster and can solve much larger problems. A heuristic based upon the branch and bound algorithm is also presented which provides fast solutions with constant performance guarantees.
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