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Job Scheduling in Logistic Warehouses
Povoda, Lukáš ; Uher, Václav (oponent) ; Karásek, Jan (vedoucí práce)
The main aim of this thesis is flow shop and job shop scheduling problem in logistics warehouses. Managing and scheduling works is currently often problem. There is no simple solution due to complexity of this problem. This problem must be resolved because of a lack efficiency of work with a higher load such as during the christmas holidays. This paper describes the methods used to solve this problem focusing mainly on the use of search algorithms, evolutionary algorithms, specifically grammar guided genetic programming. This paper describes the problem of job shop scheduling on a simple theoretical example. The implemented algorithm for solving this problem was subjected to tests inspired on data from real warehouse, as well as synthetically created tests with more jobs and a greater number of workers. Synthetic tests were generated randomly. All tests were therefore run several times and the results were averaged. In conclusion of this work are presented the results of the algorithm and the optimum parameter settings for different sizes of problems and requirements for the solution. Genetic algorithm has been extended to calculate fitness of individuals with regard to number of collisions, extended to use priority rules during run of evolution, and some parts of algorithm was parallelized.
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Optimalizační model výroby v potravinářském průmyslu
Blachová, Katrin ; Pelikán, Jan (vedoucí práce) ; Fábry, Jan (oponent)
Diplomová práce se zabývá plánováním a rozvrhováním výroby v potravinářského průmyslu. Teoretická část se zabývá formulací a strukturou rozvrhovacích úloh a detailněji rozebírá úlohu flow shop, pro kterou je vytvořena reálná aplikace pro nejmenovanou firmu. Dále také stručně popisuje technologické specifikace výroby, jež jsou stěžejní pro praktickou část. Praktická část se zabývá formulací matematického modelu. Optimální řešení je získáno pomocí optimalizačního programu MPL for Windows. Matematický model zahrnuje proměnné, které řeší sériové a paralelní řazení procesorů a snaží se zachytit co nejvěrněji výrobní procesy s technickými specifikacemi pro konkrétní podnik. Kritériem optimalizace je minimalizace nákladů z hlediska vybrané technologie výroby. Reálná aplikace slouží jako vzor pro řešení podobných úloh.
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Job Scheduling in Logistic Warehouses
Povoda, Lukáš ; Uher, Václav (oponent) ; Karásek, Jan (vedoucí práce)
The main aim of this thesis is flow shop and job shop scheduling problem in logistics warehouses. Managing and scheduling works is currently often problem. There is no simple solution due to complexity of this problem. This problem must be resolved because of a lack efficiency of work with a higher load such as during the christmas holidays. This paper describes the methods used to solve this problem focusing mainly on the use of search algorithms, evolutionary algorithms, specifically grammar guided genetic programming. This paper describes the problem of job shop scheduling on a simple theoretical example. The implemented algorithm for solving this problem was subjected to tests inspired on data from real warehouse, as well as synthetically created tests with more jobs and a greater number of workers. Synthetic tests were generated randomly. All tests were therefore run several times and the results were averaged. In conclusion of this work are presented the results of the algorithm and the optimum parameter settings for different sizes of problems and requirements for the solution. Genetic algorithm has been extended to calculate fitness of individuals with regard to number of collisions, extended to use priority rules during run of evolution, and some parts of algorithm was parallelized.
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