¹University of Technology and Life Sciences, Bydgoszcz, Poland

Correspondence: A awrynowicz, Department of Production Engineering, University of Technology and Life Sciences in Bydgoszcz, 7 Kaliskiego, 85-796 Poland. E-mail: anlaw@atr.bydgoszcz.pl

Received October 2005; Accepted March 2007; Published online 16 May 2007.

Abstract

In the traditional approaches, processes of planning and scheduling are done sequentially, where the process plan is determined before the actual scheduling is performed. This simple approach ignores the relationship between the scheduling and planning. Practical scheduling systems need to be able to react to significant real-time events within an acceptable response time and revise schedules appropriately. Therefore, the author proposes a new methodology with artificial intelligence to support production planning and scheduling in supply net. In this approach, the production planning problem is first solved, and then the scheduling problem is considered with the constraint of the solution. The approach is implemented as a combination of expert system and genetic algorithm. The research indicates that the new system yields better results in real-life supply net than using a traditional method. The results of experiments provide that the proposed genetic algorithm produces schedules with makespan that is average 21% better than the methods based on dispatching rules.