Title: Online MTO lead-time scheduling: a probabilistic approach

Authors: Zu-Hsu Lee

Addresses: Department of Management and Information Systems, Montclair State University Montclair, NJ 07043, USA

Abstract: This paper considers a lead time (or due date) scheduling problem faced by a manufacturer that produces customised products according to specific customer orders. It uses a single sever model to design an effective, yet simple heuristic procedures for both sequencing and lead time determination decisions. Typically, a series of jobs with individual arrival times and weights must be sequenced on a single machine. With each arrival, a lead time must be determined, and the job completed before the promised due date. An on-line heuristic may be developed in certain situations, based on limited information about the future, with the objective of minimising the average (or total) weighted due date for large size instances. Computational testing shows that this heuristic is more effective than the conventional scheduling rules not only for the average weighted due date, but also for the average weighted lead time, for both stable systems and heavily loaded ones.

Keywords: due date assignment; lead times; meta-heuristic; online scheduling; probabilistic analysis; queueing; make-to-order; MTO; customisation; weighted due dates.

DOI: 10.1504/IJOR.2008.016160

International Journal of Operational Research, 2008 Vol.3 No.1/2, pp.183 - 200

Published online: 07 Dec 2007 *

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