Ant colony optimization algorithm and artificial immune system applied to a robot route

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Standard

Ant colony optimization algorithm and artificial immune system applied to a robot route. / Ribeiro, J. M.S.; Silva, M. F.; Santos, M. F. et al.
Proceedings of the 2019 20th International Carpathian Control Conference, ICCC 2019. Hrsg. / Andrzej Kot; Agata Nawrocka. Piscataway: IEEE - Institute of Electrical and Electronics Engineers Inc., 2019. 8765910 (Proceedings of the 2019 20th International Carpathian Control Conference, ICCC 2019).

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Harvard

Ribeiro, JMS, Silva, MF, Santos, MF, Vidal, VF, Honorio, LM, Silva, LAZ, Rezende, HB, Santos Neto, AF, Mercorelli, P & Pancoti, AAN 2019, Ant colony optimization algorithm and artificial immune system applied to a robot route. in A Kot & A Nawrocka (Hrsg.), Proceedings of the 2019 20th International Carpathian Control Conference, ICCC 2019., 8765910, Proceedings of the 2019 20th International Carpathian Control Conference, ICCC 2019, IEEE - Institute of Electrical and Electronics Engineers Inc., Piscataway, 20st International Carpathian Control Conference - ICCC 2019, Kraków - Wieliczka, Polen, 26.05.19. https://doi.org/10.1109/CarpathianCC.2019.8765910

APA

Ribeiro, J. M. S., Silva, M. F., Santos, M. F., Vidal, V. F., Honorio, L. M., Silva, L. A. Z., Rezende, H. B., Santos Neto, A. F., Mercorelli, P., & Pancoti, A. A. N. (2019). Ant colony optimization algorithm and artificial immune system applied to a robot route. In A. Kot, & A. Nawrocka (Hrsg.), Proceedings of the 2019 20th International Carpathian Control Conference, ICCC 2019 Artikel 8765910 (Proceedings of the 2019 20th International Carpathian Control Conference, ICCC 2019). IEEE - Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CarpathianCC.2019.8765910

Vancouver

Ribeiro JMS, Silva MF, Santos MF, Vidal VF, Honorio LM, Silva LAZ et al. Ant colony optimization algorithm and artificial immune system applied to a robot route. in Kot A, Nawrocka A, Hrsg., Proceedings of the 2019 20th International Carpathian Control Conference, ICCC 2019. Piscataway: IEEE - Institute of Electrical and Electronics Engineers Inc. 2019. 8765910. (Proceedings of the 2019 20th International Carpathian Control Conference, ICCC 2019). doi: 10.1109/CarpathianCC.2019.8765910

Bibtex

@inbook{8370cc4049794e8d94641a26104b520e,
title = "Ant colony optimization algorithm and artificial immune system applied to a robot route",
abstract = "This Article aims to introduce two meta-heuristics techniques: Ant Colony Optimization (ACO) and Artificial Immune System (AIS) to find the best route for a robot. The ACO is an algorithm based on the ant food search process, and the AIS is inspired by the defending mechanism of the human organism. In order to illustrate and compare the potential of these techniques, this paper applies both techniques in a problem of determining the shortest possible route for a robot without hitting any obstacles in three different maps. According to the tests, the ACO shows better results regarding the number of iterations to reach the global optimum, while the AIS shows better results when it comes to the processing time. From the result, it can be seen that the ACO found a solution to all maps demonstrating it is an excellent choice for this problem type.",
keywords = "Ant Colony Optimization, Artificial Immune System, Heuristics Techniques, Robot, Engineering",
author = "Ribeiro, {J. M.S.} and Silva, {M. F.} and Santos, {M. F.} and Vidal, {V. F.} and Honorio, {L. M.} and Silva, {L. A.Z.} and Rezende, {H. B.} and {Santos Neto}, {A. F.} and P. Mercorelli and Pancoti, {A. A.N.}",
year = "2019",
month = may,
day = "1",
doi = "10.1109/CarpathianCC.2019.8765910",
language = "English",
isbn = "978-1-7281-0703-5 ",
series = "Proceedings of the 2019 20th International Carpathian Control Conference, ICCC 2019",
publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",
editor = "Andrzej Kot and Agata Nawrocka",
booktitle = "Proceedings of the 2019 20th International Carpathian Control Conference, ICCC 2019",
address = "United States",
note = "20st International Carpathian Control Conference - ICCC 2019, ICCC ; Conference date: 26-05-2019 Through 29-05-2019",
url = "https://iccc.agh.edu.pl/",

}

RIS

TY - CHAP

T1 - Ant colony optimization algorithm and artificial immune system applied to a robot route

AU - Ribeiro, J. M.S.

AU - Silva, M. F.

AU - Santos, M. F.

AU - Vidal, V. F.

AU - Honorio, L. M.

AU - Silva, L. A.Z.

AU - Rezende, H. B.

AU - Santos Neto, A. F.

AU - Mercorelli, P.

AU - Pancoti, A. A.N.

N1 - Conference code: 20

PY - 2019/5/1

Y1 - 2019/5/1

N2 - This Article aims to introduce two meta-heuristics techniques: Ant Colony Optimization (ACO) and Artificial Immune System (AIS) to find the best route for a robot. The ACO is an algorithm based on the ant food search process, and the AIS is inspired by the defending mechanism of the human organism. In order to illustrate and compare the potential of these techniques, this paper applies both techniques in a problem of determining the shortest possible route for a robot without hitting any obstacles in three different maps. According to the tests, the ACO shows better results regarding the number of iterations to reach the global optimum, while the AIS shows better results when it comes to the processing time. From the result, it can be seen that the ACO found a solution to all maps demonstrating it is an excellent choice for this problem type.

AB - This Article aims to introduce two meta-heuristics techniques: Ant Colony Optimization (ACO) and Artificial Immune System (AIS) to find the best route for a robot. The ACO is an algorithm based on the ant food search process, and the AIS is inspired by the defending mechanism of the human organism. In order to illustrate and compare the potential of these techniques, this paper applies both techniques in a problem of determining the shortest possible route for a robot without hitting any obstacles in three different maps. According to the tests, the ACO shows better results regarding the number of iterations to reach the global optimum, while the AIS shows better results when it comes to the processing time. From the result, it can be seen that the ACO found a solution to all maps demonstrating it is an excellent choice for this problem type.

KW - Ant Colony Optimization

KW - Artificial Immune System

KW - Heuristics Techniques

KW - Robot

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85069847968&partnerID=8YFLogxK

U2 - 10.1109/CarpathianCC.2019.8765910

DO - 10.1109/CarpathianCC.2019.8765910

M3 - Article in conference proceedings

SN - 978-1-7281-0703-5

T3 - Proceedings of the 2019 20th International Carpathian Control Conference, ICCC 2019

BT - Proceedings of the 2019 20th International Carpathian Control Conference, ICCC 2019

A2 - Kot, Andrzej

A2 - Nawrocka, Agata

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

CY - Piscataway

T2 - 20st International Carpathian Control Conference - ICCC 2019

Y2 - 26 May 2019 through 29 May 2019

ER -

DOI