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 -