INISIALISASI POPULASI PADA ALGORITMA GENETIKA MENGGUNAKAN SIMPLE HILL CLIMBING (SHC) UNTUK TRAVELING SALESMAN PROBLEM (TSP)
ABSTRACT: In classical genetic
algorithm, the determination of the initial individu generated by random
methods. In the study using a large individu, these methods often cause
undesirable effects such as premature convergence in finding the optimal
solution. In this study, algorithm Simple Hill Climbing (SHC) as the algorithm
locally optimal analyzed its application to improve the performance of the
genetic algorithm in order to avoid the genetic algorithm to the problem of
convergence premature so expect to achieve optimal solutions in solving the
Traveling Salesman Problem (TSP), In this research, three types of experiments
by applying different parameters of Genetic Algorithm.In the first experiment,
initial values obtained for the solution is 3596.6, Genetic Algorithm In the
second experimental values obtained initial solution to SHC at 3494.1, and the
best SHC for the best solution Genetic Algorithm In the third experiment
obtained the initial value of 3330.9
Penulis: Delima Sitanggang
Kode Jurnal: jptkomputerdd150428