Title: Framework for the dynamic scheduling of complex job shops

Authors: Esther Alvarez, Fernando Diaz

Addresses: Organisation Department, University of Deusto, Bilbao 48007, Spain. ' Mathematics and Applied Physics Department, University of Deusto, Bilbao 48007, Spain

Abstract: This paper discusses a Dynamic Scheduling (DS) problem in discrete manufacturing with a combined make-to-stock and make-to-order medium batch high range of products. Most of the available methodologies regarding production scheduling are either off-line methods or propose a whole rescheduling process in order to respond to disturbances. Nevertheless, static assumptions related to the manufacturing environment or customer orders seldom hold good in industrial manufacturing environments. In practice, it is very time-consuming to build new schedules to deal with these problems, so the use of approximate approaches is justified. On the one hand, Heuristic Rules (HRs) can provide good solutions to complex problems in real-time. On the other hand, Genetic Algorithms (GAs) can adapt to the time available to find a solution. In this paper, a comparison is made between HRs and GAs based on the results gathered from a prototype built in the context of a European project under the Growth programme.

Keywords: shopfloor control; genetic algorithms; GAs; unexpected events; dynamic scheduling; make-to-stock; make-to-order; job shop scheduling.

DOI: 10.1504/IJMTM.2007.013326

International Journal of Manufacturing Technology and Management, 2007 Vol.11 No.3/4, pp.411 - 425

Published online: 20 Apr 2007 *

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