Abstract
This paper attempts to solve the problem of searching minimum production order completion time variants by means of stochastic logical structures with all cost curve descent points and corresponding minimum-cost schedules. The analysis presented in this paper considers scheduling of unique and small batch production, predominantly to order, which accounts for changing requirements of the customer, the complexity and long production process makespan including its technical preparation. Scheduling of production order was performed by means of GAN networks and employed the concept of soft relations. The cost/time relation analysis is based on two-node network models using the cost curve. A new approach to scheduling under uncertainty is proposed and discussed. The problem is illustrated with an example.
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Lapunka, I., Pisz, I., Wittbrodt, P. (2018). Stochastic Scheduling of Production Orders Under Uncertainty. In: Pérez García, H., Alfonso-Cendón, J., Sánchez González, L., Quintián, H., Corchado, E. (eds) International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding. SOCO ICEUTE CISIS 2017 2017 2017. Advances in Intelligent Systems and Computing, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-319-67180-2_34
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DOI: https://doi.org/10.1007/978-3-319-67180-2_34
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