Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal International Journal of Computing Science and Applied Mathematics
Titin J. Ambarwati
Institut Teknologi Sepuluh Nopember
Computer Science & IT Education Mathematics

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
A Genetic Algorithm with Best Combination Operator for the Traveling Salesman Problem Muhammad Luthfi Shahab; Titin J. Ambarwati; Soetrisno Soetrisno; Mohammad Isa Irawan
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 5, No 2 (2019)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (390.627 KB) | DOI: 10.12962/j24775401.v5i2.5830

Abstract

In this research, we propose a genetic algorithm with best combination operator (BC(x,y)O) for the traveling salesman problem. The idea of best combination operator is to find the best combination of some disjoint sub-solutions (also the reverse of sub-solutions) from some known solutions. We use BC(2,1)O together with a genetic algorithm. The proposed genetic algorithm uses the swap mutation operator and elitism replacement with filtration for faster computational time. We compare the performances of GA (genetic algorithm without BC(2,1)O), IABC(2,1)O (iterative approach of BC(2,1)O), and GABC(2,1)O (genetic algorithm with BC(2,1)O). We have tested GA, IABC(2,1)O, and GABC(2,1)O three times and pick the best solution on 50 problems from TSPLIB. From those 50 problems, the average of the accuracy from GA, IABC(2,1)O, and GABC(2,1)O are 65.12%, 94.21%, and 99.82% respectively.
Co-Authors Mohammad Isa Irawan Shahab, Muhammad Luthfi Soetrisno Soetrisno