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Warianty tytułu
Języki publikacji
Abstrakty
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.
Wydawca
Czasopismo
Rocznik
Tom
Strony
105--112
Opis fizyczny
Bibliogr. 11 poz., rys.
Twórcy
autor
- Warsaw University of Technology Faculty of Transport Koszykowa Street 75, 00-662 Warsaw, Poland tel.: +48 22 2346017, fax: +48 22 2346017
autor
- Warsaw University of Technology Faculty of Transport Koszykowa Street 75, 00-662 Warsaw, Poland tel.: +48 22 2346017, fax: +48 22 2346017
Bibliografia
- [1] Abdoun, O., Abouchabaka, J., A Comparative Study of Adaptive Crossover Operators for Genetic Algorithms to Resolve the Traveling Salesman Problem, International Journal of Computer Applications, Foundation of Computer Science, Vol. 31, No. 11, pp. 49-57, New York, USA 2011.
- [2] Beliën, J., Boeck L., Municipal Solid Waste Collection and Management Problems: A Literature Revie, Transportation Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 48, Is. 1, pp. 78-102, USA 2014.
- [3] Bräysy, O., Gendreau M., Vehicle Routing Problem with Time Windows, Part II: Metaheuristics, Transportation Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 39, Is. 1, pp. 119-139, USA 2005.
- [4] Goldberg, D. E., Algorytmy genetyczne i ich zastosowanie, Wydawnictwo Naukowo-Techniczne, Warszawa 1995.
- [5] Goldberg, D. E., Lingle, R., Alleles, Loci, and the TSP, Proceedings of the First International Conference on Genetic Algorithms, Lawrence Erlbaum Associates, Hillsdale, pp. 154-159, NJ 1985.
- [6] Grefenstette, J. J.,Gopal, R., Rosmaita, B., Van Gucht, D., Genetic Algorithm for the TPS, Proceedings of the First International Conference on Genetic Algorithms, Lawrence Erlbaum Associates, Hillsdale, pp. 160-168, NJ 1985.
- [7] Grzymkowski, R., Kaczmarek, K., Kieltyka, S., Nowak, I., Wykłady z modelowania matematycznego. Wydawnictwo Pracowni Komputerowej Jacka Skalmierskiego, Gliwice 2008.
- [8] Jacyna, M., Modelowanie i ocena systemów transportowych, Oficyna Wydawnicza Politechniki Warszawskiej, Warszawa 2009.
- [9] Michalewicz, Z., Algorytmy genetyczne + struktury danych = programy ewolucyjne, Wydawnictwo Naukowo-Techniczne, Warszawa 1996.
- [10] Nagata, Y., Kobayashi, S., A Powerful Genetic Algorithm Using Edge Assembly Crossover for the Traveling Salesman Problem, Transportation Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 25, Is. 2, pp. 346-363, USA 2013.
- |11] Płaczek, E., Szołtysek, J., Wybrane metody optymalizacji systemu transportu odpadów komunalnych w Katowicach, LogForum, Wyższa Szkoła Logistyki, Vol. 4, pp. 1-10, Poznan 2008.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fbbbeea6-0e0f-4d27-94e3-61f924a1f560