* Corresponding Author
Hide
Show all
Sistem Penjadwalan Pertandingan Pencak Silat Berbasis Algoritma Genetika
https://doi.org/10.22146/ijccs.24214 Ari Kusuma Wardana(1*), Sri Hartati(2)
(1)
(2) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(*) Corresponding Author
Abstract
Genetic Algorithm is one of famous algorithm and often used in many sector. Usually genetic algoritm is used in solution searching about complex problems. Pencak silat macth scheduling is a complex scheduling and needs a lot of time to made it. Objective this research implements a genetic algorithm as an algorithm which can solve the problem of pencak silat macth scheduling and can satisfy all of hard constraint and minimize soft constraint.
In this research genetic algorithm roles as algorithm which solves pencak silat mach scheduling problems in Pimda 02 Tak Suci Bantul. Population which produced by genetic algorithm represents solution alternatives which offered. Best chromosome in a population represents macth scheduling solution. This solution is sequence of match partai based on rules of pencak silat match scheduling.
This research produces best fitness value ever in each generation is 1. More and more chromosom number and more and more generation number will make batter solution and batter fitness value. This research is expected helping pencak silat match committes make a pencak silat schedule in pencak silat championship.
Keywords
Full Text:
PDFReferences
[1] Deng, X., Zhang, Y., Kang, B., Wu, J., Sun, X., dan Deng, Y., 2011, An Application of Genetic Algorithm for University Course Timetabling Problem, Chinese Control and Decision Conference (CCDC), IEEE Xplore, 978-1-4244-8738-7/11.
[2] D. M. D. U. Putra and S. Subanar, “Penerapan Algoritma Genetika Untuk Menyelesaikan Permasalahan Penjadwalan Perawat Dengan Fuzzy Fitness Function,” IJCCS (Indonesian J. Comput. Cybern. Syst., vol. 6, no. 2, 2013 [Online]. Available: https://jurnal.ugm.ac.id/ijccs/article/view/2148. [Accessed: 20-Apr-2017]
[3] Kyngäs, J., Nurmi, K., 2009, Scheduling the Finnish !st Division Ice Hockey League, Proceedings of the Twenty-Second International FLAIRS Conference.
[4] Barone, L., While, L., Hughes, P., Hingston, P., 2006, Fixture-scheduling for the Australian Football League using a Multi-Objective Evolutionary Algorithm, IEEE Congress on Evolutionary Computation, 0-7803-9487-9/06.
[5] While, L., dan Barone, L., 2007, Super 14 Rugby Fixture Scheduling Using a Multi-Objective Evolutionary Algoritm. Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Scheduling, 1-4244-0704-4/07.
[6] Guangdong, H., dan Qun, W., 2011, A hibrid ACO-GA on Sports Competition Scheduling, Ant Colony Optimization - Methods and Applications, Avi Ostfeld (Ed.), ISBN: 978-953-307-157-2.
[7] Negnevitsky, M., 2005, Artificial Intelligence: A Guide to Intelligent System 2nd
Edition, Pearson Education Limited, England. ISBN 0-321-20466-2.
[8] Gen, M., dan Cheng, R., 2000, Genetic Algorithms and Engineering Optimization, John Wiley and Son, United States of America.
[9] Engelbrecht, A. P., 2002, Computational Intelligence An Introduction, John Wiley and Son, England.
[10] Obitko, M., 1998, X. Encoding, http://www.obitko.com/tutorials/genetic-algorithms/encoding.php, diakses tanggal 23 Juni 2016.
DOI: https://doi.org/10.22146/ijccs.24214
Article Metrics
Abstract views : 4728
| 
views : 5012
Refbacks
- There are currently no refbacks.
Copyright (c) 2017 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
View My Stats1