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Travelling Salesman Problem Application in Particular Logistics Enterprise
Ružička, Vladimír ; Bartík, Vladimír (referee) ; Kreslíková, Jitka (advisor)
This paper deals with optimal distribution issues. One may find listed problems of real life linked to distribution. Moreover, there are explained travelling salesman problem, vehicle routing problem and its variants. This work brings an overview of different ways how to solve vehicle routing problem. In practical part, there is an analysis of distribution of real company. The concept of application is presented in the second part of this paper. This concept could reduce costs of distribution in analyzed company. Testing is aimed mainly on the variant VRPCL (Vehicle Routing Problem with Continuos Loading).
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The Use of Artificial Intelligence in Business
Matus, Gabriel ; Doskočil, Radek (referee) ; Dostál, Petr (advisor)
This work deals with traveling salesman problem (TSP) and examines it’s possibilities to use in business. It is about the optimization of the travel cost, saving time and unnecessary mileage. Part of the work is a program with a GUI written in program MATLAB. Program uses neural networks to calculate the most effective path between places, where the trader has to reach. It’s possible to use the algorithm for many purposes, e.g. distribution of goods, store management, planning of PCBs or rescue services. Program communicates with the Google Maps API server, which provides the actual information of the path.
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Optimization of dispatch of goods from rack system of logistics warehouse.
Chlup, Jiří ; Klapka, Jindřich (referee) ; Šeda, Miloš (advisor)
The diploma thesis submitted solves problems of optimization of goods expedition from rack system of a logistic store. It concerns solution of a practical task which optimizes a passage route through the rack system and evaluates individual orders for creation of optimal expedition dispatching batch. The existing dispatching system, use of sources and creation of time schedule is being described at the beginning. Description of general practical solutions of seeking the shortest way through the graph through appointed nodes follows. Chosen solution and its practical implementation are introduced afterwards. Comparative tests with existing system and their evaluations are mentioned at the end of the thesis.
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The Application of PSO in Business
Veselý, Filip ; Kaštovský, Petr (referee) ; Dostál, Petr (advisor)
This work deals with two optimization problems, traveling salesman problem and cluster analysis. Solution of these optimization problems are applied on INVEA-TECH company needs. It shortly describes questions of optimization and some optimization techniques. Closely deals with swarm intelligence, strictly speaking particle swarm intelligence. Part of this work is recherché of variants of particle swarm optimization algorithm. The second part describes PSO algorithms solving clustering problem and traveling salesman problem and their implementation in Matlab language.
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Advanced Evolutionary Optimisation of TSP-Based Problems
Hladyuk, Vadym ; Vašíček, Zdeněk (referee) ; Bidlo, Michal (advisor)
This paper solves the traveling salesman problem using an evolutionary algorithm, specifically a genetic algorithm. It is a hybrid of the genetic algorithm, using a local search algorithm and other enhancements that further improve the results obtained. The traveling salesman problem will be solved from 20 cities to 25,000 cities. In the experiments chapter, I have determined the best settings for all the parameters in the program and properly tested their appropriateness. In the next part of the experiments chapter, I found out the performance of the full version of the genetic algorithm and its variants. In the last section, I compared the evolution of fitness values of different variants of genetic algorithms and different variants of crossover operators, I also compared the time consumption. I suggested further possible improvements either to the local search algorithm or to another approach to solve the TSP.
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Optimization of Warehouse Passing
Holáň, Jan ; Kožár, Tomáš (referee) ; Křivka, Zbyněk (advisor)
The work focuses on finding the shortest path through the warehouse in order to pick a given number of items. It describes the necessary theory related to mathematical problems related to the topic of this work. Most attention is given to a generally not much discussed topic, which is the grouping of indistinguishable groups of items, in order to obtain the resulting shortest path between items. The result is a C++ library capable of dealing with picking optimization under conditions defined by a specific real company.
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System for Service Workers’ Routes Planning
Mlčoch, Michal ; Bartík, Vladimír (referee) ; Hynek, Jiří (advisor)
This bachelor’s thesis deals with the issue of service requests arising in smart cities and their planning into the routes for service workers. The thesis discusses the issue of the concept of smart cities, route optimization and analysis of services providing route optimization. This work aims to create a system for planning the routes of service workers for the smart city platform developed by Logimic. The main functionality is to enable route optimization through third-party services, and the emphasis is on being able to easily change the thirdparty service providing the optimization.
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Travelling Salesman Problem
Řezníček, Jan ; Zbořil, František (referee) ; Zbořil, František (advisor)
The work focuses on implementing algorithms that solve the Traveling Salesman Problem. It also includes a user interface with a map for importing locations. The main algorithms that are part of the work are ACO and an algorithm that I have devised and implemented. ACO optimization improves results, such as setting initial pheromone levels using the nearest neighbor algorithm. My algorithm works on the principle of gradually improving the path.
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Genetic Algorithms driven by MCTS
Havránek, Štěpán ; Hric, Jan (advisor) ; Moudřík, Josef (referee)
Evolutionary and genetic algorithms are problem-solving methods designed according to a nature inspiration. They are used for solving hard problems that we cannot solve by any efficient specialized algorithm. The Monte Carlo method and its derivation the Monte Carlo Tree Search (MCTS) are based on sampling and are also commonly used for too complex problems, where we are dealing with enormous memory consumption and it is impossible to perform a complete searching. The goal of this thesis is to design a general problem solving method that is built from these two completely different approaches. We explain and implement the new method on one example problem: the Traveling salesman problem (TSP). Second part of this thesis contains various tests and experiments. We compare different settings and parametrizations of our method. The best performing variant is then compared with the classical evolutionary TSP solution or, for example, with greedy algorithms. Our method shows competitive results. The best results were achieved with the cooperation of our method and the classical evolutionary TSP solution. This union shows better results than any of its parts separately, which we find as a great success.
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