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Optimizacija avtomatskih skladiščnih sistemov
Kulovic, Jože (Author), Lotrič, Uroš (Mentor) More about this mentor... This link opens in a new window

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Abstract
V magistrskem delu smo razvili metode za optimizacijo razporeditve opravil skladiščnih sistemov v realnem času. Optimizacijo smo opravljali na podlagi obratujočega skladišča, iz katerega smo dobili vse specifikacije, tako da smo pri sami optimizaciji upoštevali tudi fizikalne lastnosti skladišča in naprav v njem. Skladiščna naprava za premikanje transportno skladiščnih enot izbranega skladiščnega sistema ima možnost sočasnega premikanja dveh transportno skladiščnih enot, kar nam daje veliko možnosti za optimizacijo. Za optimizacijo razporeditve opravil smo uporabili Dijkstrov algoritem, Bellman-Fordov algoritem, genetski algoritem, optimizacijo s kolonijami mravelj, algoritem A* in algoritem soseščine. Najboljše rezultate smo dosegli z algoritmom soseščine, ki temelji na odločitvenem pristopu. Optimizacijo razporeditve petstotih opravil je opravil v manj kot eni sekundi, pri tem pa smo dosegli 20 % pohitritev v primeru časovne optimizacije. V primeru energijske optimizacije pa smo porabo energije optimizirali za kar 40 %.

Language:Slovenian
Keywords:avtomatizirano skladišče, dodeljevanje prostora, optimizacija, genetski algoritem, hevristični algoritem, primerjava algoritmov, računalništvo in informatika, optimizacija
Work type:Master's thesis/paper (mb22)
Organization:FRI - Faculty of computer and information science
Year:2016
Views:1066
Downloads:536
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Secondary language

Language:English
Title:Optimisation of automated warehouse systems
Abstract:
In the master thesis we developed methods for optimizing tasks assignment in high bay warehouse system. Optimization was performed based on a real warehouse system from which we acquired all specifications. In our optimization we took into account all physical properties of the warehouse from the specification. Warehouse device for moving transport storage units in the selected warehouse can move two transport units at the same time, giving us a lot of optimization options. To optimize tasks assignment we used Dijkstra algorithm, Bellman-Ford algorithm, genetic algorithm, ant colony optimization algorithm, algorithm A* and neighborhood algorithm. We achieved the best result using neighborhood algorithm based on decision-making approach. Optimization of five hundred tasks was done in less than one second, and with it we increased task execution speed by 20 % and optimized energy consumption by 40 % .

Keywords:automated warehouse, warehouse storage allocation, optimization, genetic algorithm, heuristic algorithm, algorithm comparison, computer science, optimization

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