Framework for the dynamic scheduling of complex job shops Online publication date: Fri, 20-Apr-2007
by Esther Alvarez, Fernando Diaz
International Journal of Manufacturing Technology and Management (IJMTM), Vol. 11, No. 3/4, 2007
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.
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