Abstract
This paper introduces process planning, scheduling and optimization in warehouse environment. The leading companies of the logistics warehouse industry still do not use planning and scheduling by automatic computer methods. Processes are planned and scheduled by an operational manager with detailed knowledge of the problem, processed tasks and commodities, warehouse layout, performance of employees, parameters of equipment etc. This is a quantum of information to be handled by a human and it can be very time-consuming to plan every process and schedule the timetable. The manager is usually also influenced by stress conditions, especially by the time of holidays when everyone is making supplies and the performance of the whole warehouse management goes down. The main contribution of this work is (a) to introduce the novel automatic method for optimization based on the evolutionary method called genetic programming, (b) to give a description of a tested warehouse, and (c) to show the metrics for performance measurement and to give a results which states the baseline for further research.
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Acknowledgments
This research work is funded by projects SIX CZ.1.05/2.1.00/03.0072, MPO FR-TI1/444, and project FEKT-S-11-17.
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Karasek, J., Burget, R., Povoda, L. (2014). Logistic Warehouse Process Optimization Through Genetic Programming Algorithm. In: Silhavy, R., Senkerik, R., Oplatkova, Z., Silhavy, P., Prokopova, Z. (eds) Modern Trends and Techniques in Computer Science. Advances in Intelligent Systems and Computing, vol 285. Springer, Cham. https://doi.org/10.1007/978-3-319-06740-7_3
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DOI: https://doi.org/10.1007/978-3-319-06740-7_3
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