TY - GEN
T1 - Solving Bi-objective quadratic assignment problem with squirrel search algorithm
AU - Ningtiyas, Sri Wahyuni
AU - Pratiwi, Asri Bekti
AU - Damayanti, Auli
N1 - Publisher Copyright:
© 2021 American Institute of Physics Inc.. All rights reserved.
PY - 2021/2/26
Y1 - 2021/2/26
N2 - The simplest model of multi-objective quadratic assignment problems, bi-objective quadratic assignment problem, is discussed in this paper. Weighted sum method is used in order to change the multi-objectives model into single-objective model. An algorithm inspired from the foraging strategy and gliding mechanism called squirrel search algorithm is proposed to solve this problem. The squirrel search algorithm parameters, such as number of iterations, number of flying squirrels and control parameter, predator presence probability, are observed by managing computational experiment to solve bi-objective quadratic assignment problem. The computational results show that general parameters, number of iteration and flying squirrels, affect the performance of the algorithm in solving this problem. Moreover, probability of predator presence which is as control parameter in this algorithm can bring better result when using smaller value of probability.
AB - The simplest model of multi-objective quadratic assignment problems, bi-objective quadratic assignment problem, is discussed in this paper. Weighted sum method is used in order to change the multi-objectives model into single-objective model. An algorithm inspired from the foraging strategy and gliding mechanism called squirrel search algorithm is proposed to solve this problem. The squirrel search algorithm parameters, such as number of iterations, number of flying squirrels and control parameter, predator presence probability, are observed by managing computational experiment to solve bi-objective quadratic assignment problem. The computational results show that general parameters, number of iteration and flying squirrels, affect the performance of the algorithm in solving this problem. Moreover, probability of predator presence which is as control parameter in this algorithm can bring better result when using smaller value of probability.
UR - http://www.scopus.com/inward/record.url?scp=85102524305&partnerID=8YFLogxK
U2 - 10.1063/5.0042202
DO - 10.1063/5.0042202
M3 - Conference contribution
AN - SCOPUS:85102524305
T3 - AIP Conference Proceedings
BT - International Conference on Mathematics, Computational Sciences and Statistics 2020
A2 - Alfiniyah, Cicik
A2 - Fatmawati, null
A2 - Windarto, null
PB - American Institute of Physics Inc.
T2 - International Conference on Mathematics, Computational Sciences and Statistics 2020, ICoMCoS 2020
Y2 - 29 September 2020
ER -