TY - GEN
T1 - Estrategia de optimización con algoritmo genético para ruta corta sin corte en el espacio finito
AU - Eduardo, Huarote Zegarra Raúl
AU - Yensi, Vega Luján
AU - Patricia, Romero Valencia Mónica
AU - Aradiel, Castañeda Hilario
AU - José, Flores Masías Edward
AU - Cesar, Larios Franco Alfredo
AU - Huaman, Jhonatan Isaac Vargas
N1 - Publisher Copyright:
© 2021 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.
PY - 2021
Y1 - 2021
N2 - By having different points in a specific space, the need arises to go through them taking as a reference the problem of the traveling agent, so also arises another problem in the journey in space, which is the risk that the paths intersect in space, therefore the research presents to solve it applies a strategy to the genetic algorithm to avoid these cuts, where the advantage of not competing all against all was taken advantage of, but from a small population the universe of cases is traversed, finding the best possible route in space avoiding these cuts. Taking into account the functions of the genetic algorithm these problems were solved using the strategy of bringing from the previous generation a pair of better individuals to the current generation. Considering if you have 50 nodes in space we managed to solve in 15.1 sec, generating a sequence of duration and depending on the x nodes in the linear equation of y = 0.3134x + 0.733, with R2 = 0.978, thus also for the variance method reflects the equation y = 0,0009x3 - 0,1256x2 + 6,1963x - 36,563, con R2 = 0,9349. Managing to find the best optimal route in finite space solving the problems found.
AB - By having different points in a specific space, the need arises to go through them taking as a reference the problem of the traveling agent, so also arises another problem in the journey in space, which is the risk that the paths intersect in space, therefore the research presents to solve it applies a strategy to the genetic algorithm to avoid these cuts, where the advantage of not competing all against all was taken advantage of, but from a small population the universe of cases is traversed, finding the best possible route in space avoiding these cuts. Taking into account the functions of the genetic algorithm these problems were solved using the strategy of bringing from the previous generation a pair of better individuals to the current generation. Considering if you have 50 nodes in space we managed to solve in 15.1 sec, generating a sequence of duration and depending on the x nodes in the linear equation of y = 0.3134x + 0.733, with R2 = 0.978, thus also for the variance method reflects the equation y = 0,0009x3 - 0,1256x2 + 6,1963x - 36,563, con R2 = 0,9349. Managing to find the best optimal route in finite space solving the problems found.
KW - Genetic algorithm
KW - Route
KW - Space
KW - Strategy
UR - http://www.scopus.com/inward/record.url?scp=85122012668&partnerID=8YFLogxK
U2 - 10.18687/LACCEI2021.1.1.354
DO - 10.18687/LACCEI2021.1.1.354
M3 - Contribución a la conferencia
AN - SCOPUS:85122012668
T3 - Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
BT - 19th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology
A2 - Larrondo Petrie, Maria M.
A2 - Zapata Rivera, Luis Felipe
A2 - Aranzazu-Suescun, Catalina
T2 - 19th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: "Prospective and Trends in Technology and Skills for Sustainable Social Development" and "Leveraging Emerging Technologies to Construct the Future", LACCEI 2021
Y2 - 19 July 2021 through 23 July 2021
ER -