Analisis Komparasi Genetic Algorithm dan Firefly Algorithm pada Permasalahan Quadratic-Assignment-Problem (QAP)

Abstract

Quadratic Assignment Problem (QAP) is the problem of determining the location of several facilities to a certain number of places to minimize the cost of moving. This displacement considers the flow of material or people movement and the distance between locations. Many studies have developed several efficient methods for solving QAP, one of which is metaheuristics. In this paper, the metaheuristic methods used are Genetic Algorithm (GA) and Firefly Algorithm (FA). The data used is taken from the Nugent data on QAPLIB with 12x12, 16x16, 20x20, and 30x30 matrices. This study proves that FA is an algorithm that produces the most optimal results with indicators in the test getting the best results (12x12 and 16x16), having better average and deviation values and faster computational time than GA. Meanwhile, for comparing the results obtained by the Nugent, FA also has more optimal results on the 12x12 and 16x16 matrices. However, the 20x20 and 30x30 GA metrics get more optimal results.