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KARÁSEK, J. BURGET, R. POVODA, L.
Originální název
Logistic Warehouse Process Optimization through Genetic Programming Algorithm
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
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 inuenced 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.
Klíčová slova
Genetic Programming, Logistics, Optimization, Scheduling
Autoři
KARÁSEK, J.; BURGET, R.; POVODA, L.
Rok RIV
2014
Vydáno
28. 4. 2014
Nakladatel
Springer
ISBN
978-3-319-06739-1
Kniha
Advances in Intelligent Systems and Computing, Modern Trends and Techniques in Computer Science
Edice
285
Strany od
29
Strany do
40
Strany počet
12
BibTex
@inproceedings{BUT105788, author="Jan {Karásek} and Radim {Burget} and Lukáš {Povoda}", title="Logistic Warehouse Process Optimization through Genetic Programming Algorithm", booktitle="Advances in Intelligent Systems and Computing, Modern Trends and Techniques in Computer Science", year="2014", series="285", pages="29--40", publisher="Springer", doi="10.1007/978-3-319-06740-7\{_}3", isbn="978-3-319-06739-1" }