TY - GEN
T1 - Solving the manufacturing cell design problem using the artificial bee colony algorithm
AU - Soto, Ricardo
AU - Crawford, Broderick
AU - Vásquez, Leandro
AU - Zulantay, Roberto
AU - Jaime, Ana
AU - Ramírez, Maykol
AU - Almonacid, Boris
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - The manufacturing cell design problem (MCDP) proposes to divide an industrial production plant into a number of manufacturing cells. The main objective is to identify an organization of machines and parts in a set of manufacturing cells to allow the transport of parts to be minimized. In this research, the metaheuristic algorithm called Artificial Bee Colony (ABC) is implemented to solve the MCDP. The ABC algorithm is inspired by the ability of bees to get food, the way they look for it and exploit it. We performed two types of experiments using two and three cells, giving a total of 90 problems that have been used to solve the MCDP using ABC. In the results experiments, good results are obtained solving the 90 proposed problems and reaching the 90 global optimum values. Finally, the results are contrasted with two classical metaheuristics and two modern metaheuristics.
AB - The manufacturing cell design problem (MCDP) proposes to divide an industrial production plant into a number of manufacturing cells. The main objective is to identify an organization of machines and parts in a set of manufacturing cells to allow the transport of parts to be minimized. In this research, the metaheuristic algorithm called Artificial Bee Colony (ABC) is implemented to solve the MCDP. The ABC algorithm is inspired by the ability of bees to get food, the way they look for it and exploit it. We performed two types of experiments using two and three cells, giving a total of 90 problems that have been used to solve the MCDP using ABC. In the results experiments, good results are obtained solving the 90 proposed problems and reaching the 90 global optimum values. Finally, the results are contrasted with two classical metaheuristics and two modern metaheuristics.
KW - Animal behavior
KW - Artificial bee colony
KW - Cell formation problem
KW - Metaheuristic
KW - Nature inspired algorithms
UR - http://www.scopus.com/inward/record.url?scp=85034254602&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-69456-6_39
DO - 10.1007/978-3-319-69456-6_39
M3 - Conference contribution
AN - SCOPUS:85034254602
SN - 9783319694559
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 473
EP - 484
BT - Multi-disciplinary Trends in Artificial Intelligence - 11th International Workshop, MIWAI 2017, Proceedings
A2 - Phon-Amnuaisuk, Somnuk
A2 - Ang, Swee-Peng
A2 - Lee, Soo-Young
PB - Springer Verlag
T2 - 11th Multi-disciplinary International Workshop on Artificial Intelligence, MIWAI 2017
Y2 - 20 November 2017 through 22 November 2017
ER -