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

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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 multi-chromosome 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.

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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

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Pentingnya Keamanan

Komputer Dalam

Penerapan Teknologi

Informasi dan

Komunikasi di

Dunia Pendidikan

Nasional Pasca Sarjana Teknik Informatika (2015)

Mempercepat Koneksi Internet

melalui Mozilla

Firefox dan

Nasional Pasca Sarjana Teknik Informatika (2015)

Sistem Operasi

Mobile Berbasis

Cloud Computing

Pengkajian dan Pengembangan

Network Melalui

Browser Mozilla

Firefox dan

Reserving

Bandwith Pada

Sistem Operasi

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