Scheduling of Re-entrant Lines with Neuro-Dynamic Programming Based on a New Evaluating Criterion

Abstract

Scheduling of re-entrant lines is very important for manufacturing systems. For some dynamic scheduling methodologies, it is necessary to model a production system with finite-state discrete-time Markov process. However, proper state cannot be found as absorbing state of Markov process when general Mean Output Rate is employed as an evaluating criterion. Mean-Output-parts Number Before First Block is presented to be a new evaluating criterion in this paper to evaluate scheduling policies for Closed Re-entrant Lines(CRL). Simulations of four static scheduling policies verify the new criterion. In order to apply a Neuro-Dynamic Programming (NDP) method to scheduling of a CRL, cost-to-go value function and transition cost function are presented as new forms under the new criterion. In addition, the policy obtained in a less-number parts system by the NDP is applied in a more-number parts system directly, whose results are satisfactory.