Abstract
In this paper we discuss an optimization approach to a real-world production planning problem. Based on raw data from instances of production planning we have developed an architecture for optimization of production planning and scheduling for manufacturing lines in small/medium enterprises (SME). The approach referred to as “Unified Planning using Intelligent Techniques”-abbreviated UPlanIT is based on genetic algorithms (GA). The schedules are constructed using rules in which the priorities are determined by the GA, using a procedure that generates parameterized activities. The approach is tested on a set of real standard production instances. The results validate the effectiveness of the proposed algorithm.
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Maleki-Dizaji, S., Nyongesa, H., Khazaei, B. (2008). UPlanIT: An Evolutionary Based Production Planning and Scheduling System. In: Krasnogor, N., Nicosia, G., Pavone, M., Pelta, D. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2007). Studies in Computational Intelligence, vol 129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78987-1_40
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DOI: https://doi.org/10.1007/978-3-540-78987-1_40
Publisher Name: Springer, Berlin, Heidelberg
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