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Applications of PSO-Based Algorithms
Hudecová, Patrícia ; Husa, Jakub (referee) ; Bidlo, Michal (advisor)
This work aimed to study already existing optimization algorithms from the field of algorithms inspired by collective behavior and apply them to problems usable in practice in practice. Subsequent efforts to improve existing solutions with possible modifications and evaluation of the results. The algorithms chosen were particle swarm optimization, gravitational search algorithm, and black hole algorithm. The optimization problems were the traveling salesman problem and knapsack, which are applicable in various practical fields.
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Stuff Placing Optimization for Transport
Vacek, Michal ; Smrčka, Aleš (referee) ; Křena, Bohuslav (advisor)
This bachelor thesis treats of application of stuff placing optimization for transport. Application is developed in cooperation with Škoda Auto a.s., which solves the problem of transport materials in containers from their factories to assembly halls abroad. It describes an application analysis, a plan and an implementation. Application consist of two parts. The first computes the optimalization - it selects subset from set of moduls (boxes) and it locates this boxes to a container. The second part of application display the stuff placing. The part of this bachelor thesis is also set of agnated optimalization methods, mainly Knapsack and Bin-packing problem.
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Particle Swarm Optimization on GPUs
Záň, Drahoslav ; Petrlík, Jiří (referee) ; Jaroš, Jiří (advisor)
This thesis deals with a population based stochastic optimization technique PSO (Particle Swarm Optimization) and its acceleration. This simple, but very effective technique is designed for solving difficult multidimensional problems in a wide range of applications. The aim of this work is to develop a parallel implementation of this algorithm with an emphasis on acceleration of finding a solution. For this purpose, a graphics card (GPU) providing massive performance was chosen. To evaluate the benefits of the proposed implementation, a CPU and GPU implementation were created for solving a problem derived from the known NP-hard Knapsack problem. The GPU application shows 5 times average and almost 10 times the maximum speedup of computation compared to an optimized CPU application, which it is based on.
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Stuff Placing Optimization for Transport
Vacek, Michal ; Smrčka, Aleš (referee) ; Křena, Bohuslav (advisor)
This bachelor thesis treats of application of stuff placing optimization for transport. Application is developed in cooperation with Škoda Auto a.s., which solves the problem of transport materials in containers from their factories to assembly halls abroad. It describes an application analysis, a plan and an implementation. Application consist of two parts. The first computes the optimalization - it selects subset from set of moduls (boxes) and it locates this boxes to a container. The second part of application display the stuff placing. The part of this bachelor thesis is also set of agnated optimalization methods, mainly Knapsack and Bin-packing problem.
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Particle Swarm Optimization on GPUs
Záň, Drahoslav ; Petrlík, Jiří (referee) ; Jaroš, Jiří (advisor)
This thesis deals with a population based stochastic optimization technique PSO (Particle Swarm Optimization) and its acceleration. This simple, but very effective technique is designed for solving difficult multidimensional problems in a wide range of applications. The aim of this work is to develop a parallel implementation of this algorithm with an emphasis on acceleration of finding a solution. For this purpose, a graphics card (GPU) providing massive performance was chosen. To evaluate the benefits of the proposed implementation, a CPU and GPU implementation were created for solving a problem derived from the known NP-hard Knapsack problem. The GPU application shows 5 times average and almost 10 times the maximum speedup of computation compared to an optimized CPU application, which it is based on.
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