Analisis Kinerja Greedy Crossover (Gx) Pada Algoritma Genetika Untuk Rostering

95

DAFTAR PUSTAKA

Gen, M. & R. Cheng. 2000. Genetic Algorithm and Engineering Optimization. Jhon
Wiley and Sons. Inc. Newyork.
Goldberg, D. E. 1989. Genetic Algorithms in Search, Optimization, and Machine
Learning. United State of America : Addison-Westley.
Goldberg, D. E. & Richardson, J. 1997. Genetic algorithms with sharing for
multimodal function optimization, Proceedings of the 2nd International
Conference on Genetic algorithms and their application : pp. 41 -49.
Grefenstette, J., Gopal, R., Rosmaita, B. & VanGucht, D. 1985. Genetic algorithms
for the travelling salesman problem. Proceeding the 1st International
Conference on Genetic Algorithms, pp:160-168.
Haupt, R. L. & Haupt. 2004. Practical Genetic Algorithmns. New Yersey: Jhon Wiley
dan Sons,Inc.
Holland, J. H. 1975. Adaptation in Natural and Artificial Systems, Ann Arbor, MI,
University of Michigan press.
Hopgood, A. A. 2001. Intelligent System for Engineers and Scientist. Boca Raton:
CRC Press LLC.
Ismkhan, H. & Zamanifar, K. 2012. Developing improved greedy crossover to solve

symmetric travelling salesman problem. International Journal of Computer
Science Issues (IJCSI)9(3): 121-126.
Kamus Besar Bahasa Indonesia. 1995. Departemen Pendidikan dan kebudayaan :
Jakarta.
Kumar, R. 2012. Novel encoding scheme in genetic algorithms for better fitness.
International Journal of Engineering and Advanced Technology (IJEAT). 1(6) :
2249 – 8958.
Kumar, V., Dutta, D., Roy, R. & Choudhury, K. 2013. An overview of methods
maintaining diversity in genetic algorithms. International Journal of Advanced
Research in Computer Science and Software Engineering. 3(3) : 430- 434.
Kühn, M., Severin, T. & Salzwedel, H. 2013. Variable mutation rate at genetic
algorithms: introduction of chromosome fitness in connection with multichromosome representation. International Journal of Computer Applications
72(17) : 0975 – 8887.
Malhotra, R., Singh, N. & Singh, Y. 2011. Genetic algorithms concepts, design for
optimization of process controllers. Journal of Computer and Information
Science. 4( 2): 39-57.
Malik., S. & Wadhwa, S. 2014. Preventing premature convergence in genetic
algorithm using DGCA and elitist technique. International Journal of Advanced
Research in computer Science and Software Engineering4(6): 410-418.
Ongko, E. 2015. Analisis performance atas metode arithmeticcrossover dalam

algoritma genetika. Tesis. Universitas Sumatera Utara.
Otman, A. & Jaafar, A. 2011. A comparative study of adaptive crossover operators for
genetic algorithms to resolve the travelling salesman problem. International
Journal of Computer Applications (0975-8887) 31(11): 49-57.

Universitas Sumatera Utara

96

Pedro, H. & Gomez, B. 2007. An efficient method based on genetic algorithms to
solve sensor network optimization problem. International Journal of Open
Problem Computational Mathematic. 3 (1) : 28-41.
Ramadan, S.Z. 2013. Reducing premature convergence problem in genetic algorithm:
Application on travel salesman problem. Computer and Information Science 6
(1): 47-57.
Rachmawati, D. & Candra, A. 2013. Implementasi Algoritma Greedy untuk
menyelesaikan masalah knapsack problem. Jurnal SAINTIKOM 12 (3).
Rexhepi, A., Maxhuni, A. & Dika, A. 2013. Analysis of the impact of parameters
values on the genetic algorithm for TSP.IJCSI (International Journal of
Computer Science Issue).10 (1) : 158-165.

Ross, P., Dave C., Hsiao L. F. 2006. Succesful Lecture Timetabling with
Evolutionary Algorithms. Departement of Artificial Intelligence, University of
Edinburgh, U. K.
Sallabi, O.,M. & El-Haddad, Y. 2009. An Improved Genetic Algorithm to Solve the
Traveling Salesman Problem. Journal world academy of science, engineering
and technology 52 (3) : 471-474
Sharma, P., Wadha, A. & Komal. 2014. Analysis of selection schemes for solving and
optimization problem in genetic algorithm. International Journal of Computer
Applications. 93 (11): 0975 – 8887.
Sivanandan, S. 2008. Introduction to Genetic Algorithm. New York: Springer Berlin
Heidelberg.
Varnamkasthi, M. J. & Lee, L. S. 2012. A fuzzy genetic algorithm based on binary
encoding for solving multidimensional knapsack problems. Journal of Applied
Mathematics. 2012 (6) : 1-24.
Xinyang Deng, Y. Z. 2011. An Application of Genetic algorithm for University
Course Timetabling Problem. IEEE Transactions on Software Engineering. Hal.
2119-2122.

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LAMPIRAN 1

AKTIFITAS KEGIATAN ILMIAH / SEMINAR
No.
1.

2.

3.

4.

Nama
Seminar/Jurnal
Konferensi
Nasional
Pengembangan
teknologi

Informasi dan
Komunikasi
(2014)

Judul
Karya Ilmiah
Pentingnya
Keamanan
Komputer Dalam
Penerapan
Teknologi
Informasi
dan
Komunikasi
di
Dunia Pendidikan
Seminar
Mempercepat
Nasional Pasca Koneksi
Internet

Sarjana Teknik melalui
Mozilla
Informatika
Firefox
dan
menghilangkan
(2015)
Reserving
Bandwith

Penulis

Tempat

Tanggal

Eva
Desiana

Hotel

Caribian
Medan

08
November
2014

1.
Eva
Desiana
2.
Grace
Lamudur
Arta
Sihombing

Gedung S3 30 Oktober
2015
Teknik
Informatika

Universitas
Sumatera
Utara

Seminar
Sistem
Operasi 1.Grace
Nasional Pasca Mobile
Berbasis
Lamudur
Sarjana Teknik Cloud Computing
Arta
Informatika
Sihombing
(2015)
2.Eva
Desiana
Eva
Seminar Hasil Penggunaan
Desiana

Configuration
Penelitian
Balai
Besar Network Melalui
Mozilla
Pengkajian dan Browser
dan
Pengembangan Firefox
Reserving
Komunikasi
Bandwith
Pada
dan
Sistem
Operasi
Informatika
Windowss7 dalam
(BBPPKI)
Mempercepat
Medan 2015

Koneksi Internet

Gedung S3 30 Oktober
2015
Teknik
Informatika
Universitas
Sumatera
Utara
Kantor
Kementrian
Komunikasi
dan
InformatikaRI Medan

Desember
2015

Universitas Sumatera Utara