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Wyszukujesz frazę "genetic optimization algorithm" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Optimizing the number of docks at transhipment terminals using genetic algorithm
Autorzy:
Izdebski, M.
Jacyna-Gołda, I.
Powiązania:
https://bibliotekanauki.pl/articles/242009.pdf
Data publikacji:
2017
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
transhipment terminal
genetic algorithm
optimization
cross docking
Opis:
This article presents the issue of designating the number of docks at the transhipment terminals using genetic algorithm. Transhipment terminals refer to cross-docking terminals. The main factor that influences on the number of these docks is the stream of cargo flowing into the given terminal. In order to determine this flow of cargo the mathematical model of the distribution of this flow was developed. This model takes into account constraints like those that e.g. processing capacity at the transhipment terminal cannot be exceeded or demand of recipients must be met. The criterion function in this model determines the minimum cost of the flow of cargo between all objects in the transport network. To designate the optimal stream of cargo flowing into the transport network the genetic algorithm was developed. In this article, the stages of construction of this algorithm were presented. The structure processed by the algorithm, the process of crossover and mutation were described. In the article in order to solve the problem of designating the number of docks at the transhipment terminals the genetic algorithm was developed.
Źródło:
Journal of KONES; 2017, 24, 4; 369-376
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Use of computer assistance in order to designate the tasks in the municipal services companies
Autorzy:
Izdebski, M.
Jacyna, M.
Powiązania:
https://bibliotekanauki.pl/articles/241863.pdf
Data publikacji:
2014
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
municipal services companies
transport
optimization
genetic algorithm
verification
Opis:
In this article, the method of designating the tasks in the municipal services companies was described. Presented method consists of three phase: the preparatory phase, the optimization phase and the generated tasks phase. Each phase was characterized. In this paper, the mathematical model of this problem was presented. The function of criterion and the condition on designating the tasks were defined. The minimum route described in the optimization phase was designated by the genetic algorithm. In this paper, the stages of constructing of the genetic algorithm were presented. A structure of the data processed by the algorithm, a function of adaptation, a selection of chromosomes, a crossover, a mutation and an inversion were characterized. A structure of the data was presented as string of natural numbers. In selection process, the roulette method was used and in the crossover, process the operator PMX was presented. The method was verified in programming language C #. The process of verification was divided into two stages. In the first stage, the best parameters of the genetics algorithm were designated. In the second stage, the algorithm was started with these parameters and the result was compared with the random search algorithm. The random search algorithm generates 2000 routes and the best result is compared with the genetic algorithm. The influence of the inversion, the mutation and the crossover on quality of the results was examined.
Źródło:
Journal of KONES; 2014, 21, 2; 105-112
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The application of genetic algorithm in the assignment problems in the transportation company
Autorzy:
Izdebski, M.
Jacyna, M.
Powiązania:
https://bibliotekanauki.pl/articles/247149.pdf
Data publikacji:
2018
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
assignment problem
genetic algorithm
multi-criterion optimization
transportation company
Opis:
The article presents the problem of the task assignment of the vehicles for the transportation company, which deals with the transport of the cargo in the full truckload system. The presented problem is a complex decision making issue which has not been analysed in the literature before. There must be passed through two stages in order to solve the task assignment problem of the vehicles for the transportation company. The first stage is to designate the tasks, the other one is to determine the number of the vehicles that perform these tasks. The task in the analysed problem is defined as transporting the cargo from the suppliers to the recipients. The transportation routes of the cargo must be determined. In order to solve the task assignment problem of the vehicles, the genetic algorithm has been developed. The construction stages of this algorithm are presented. The algorithm has been developed to solve the multi-criteria decision problem. What is more, the algorithm is verified by the use of the real input data.
Źródło:
Journal of KONES; 2018, 25, 4; 133-140
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-parametric and multi-objective thermodynamic optimization of a spark-ignition range extender ICE
Autorzy:
Toman, R.
Brankov, I.
Powiązania:
https://bibliotekanauki.pl/articles/243112.pdf
Data publikacji:
2018
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
Range Extender
hybrid electric vehicle
battery electric vehicle
internal combustion engine
spark ignition
thermodynamic optimization
genetic algorithm
Opis:
The current legislation pushes for the increasing level of vehicle powertrain electrification. A series hybrid electric vehicle powertrain with a small Range Extender (REx) unit – comprised of an internal combustion engine and an electric generator – has the technical potential to overcome the main limitations of a pure battery electric vehicle: driving range, heating, and air-conditioning demands. A typical REx ICE operates only in one or few steady-states operating points, leading to different initial priorities for its design. These design priorities, compared to the conventional ICE, are mainly NVH, package, weight, and overall concept functional simplicity – hence the costeffectiveness. The design approach of the OEMs is usually rather conservative: parting from an already-existing ICE or components and adapting it for the REx application. The fuel efficiency potential of a one-point operation of the REx ICE is therefore not fully exploited. This article presents a multi-parametric and multi-objective optimization study of a REx ICE. The studied ICE concept uses a well-known and proven technology with a favourable production and development costs: it is a two-cylinder, natural aspirated, port injected, four-stroke SI engine. The goal of our study is to find its thermodynamic optimum and fuel efficiency potential for different feasible brake power outputs. Our optimization tool-chain combines a parametric GT-Suite ICE simulation model and modeFRONTIER optimization software with various optimization strategies, such as genetic algorithms, gradient based methods or various hybrid methods. The optimization results show a great fuel efficiency improvement potential by applying this multi-parametric and multi-objective method, converging to interesting short-stroke designs with Miller valve timings.
Źródło:
Journal of KONES; 2018, 25, 3; 459-466
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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