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Job Scheduling in Logistic Warehouses
Povoda, Lukáš ; Uher, Václav (referee) ; Karásek, Jan (advisor)
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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Optimization model of production in food industry
Blachová, Katrin ; Pelikán, Jan (advisor) ; Fábry, Jan (referee)
The thesis deals with planning and scheduling of production in the food industry. The theoretical part is concerned with the formulation and structure of the task scheduling and analyses the flow shop in the detail, for which a real application for an unnamed company has been created. It also briefly describes the technical specifications of production, which are crucial for the practical part. The practical part deals with the formulation of a mathematical model. The optimal solution is obtained using the optimization program MPL for Windows. Mathematical model includes variables that solves serial and parallel processors and try to capture as most exact as possible manufacturing processes with the technical specifications for a particular enterprise. The criterion for optimization is to minimize the cost in terms of the selected technology of production.
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Job Scheduling in Logistic Warehouses
Povoda, Lukáš ; Uher, Václav (referee) ; Karásek, Jan (advisor)
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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