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Journal : Jurnal TIMES

INISIALISASI POPULASI PADA ALGORITMA GENETIKA MENGGUNAKAN SIMPLE HILL CLIMBING (SHC) UNTUK TRAVELING SALESMAN PROBLEM (TSP) Sitanggang, Delima
Jurnal TIMES Vol 4, No 2 (2015)
Publisher : STMIK TIME

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (209.85 KB)

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
INISIALISASI POPULASI PADA ALGORITMA GENETIKA MENGGUNAKAN SIMPLE HILL CLIMBING (SHC) UNTUK TRAVELING SALESMAN PROBLEM (TSP) Delima Sitanggang
Jurnal TIMES Vol 4 No 2 (2015)
Publisher : STMIK TIME

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (209.85 KB)

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
Co-Authors -, Amalia ., Calvin ., Efendy ., Kelvin Abdi Dharma Achmad Ridwan, Achmad Ade Sahputra Nababan Agung Prabowo Agustinus Lumban Raja Albert Sagala, Albert Alvina, Jesslyn Ambarita, Rivandu Amir Mahmud Husein, Mawaddah Harahap, Amir Angie, Vicky Anita Anita Anita Christine Sembiring Ayu Rahayu Sagala Ayu Rosalya Sagala Barus, Ertina Sabarita Bolon, Debby Novriyanti Br Tp. Butarbutar, Serly Yunarti Cloudia Stevani Saragih Sumbayak Cristian Andika Tarigan Dafa', Mu'ammar Dahlian, Ryo Benhard David David Debby Novriyanti Br Tp.Bolon Djuli, Zachary Esther Mayorita Nababan Etriska Prananta S. Evta Indra Evta Indra Faijriah Nazla Sahira Felix Felix Ginting, Arico Sempana Ginting, Nessa Sanjaya Ginting, Riski Titian Grace Aloina Greace HS, Christnatalis Hutahaean, Rani Hutasoit, Feliks Daniel Iboy Erwin Saragih, Rijois Immanuel Sinaga, Ferdy Indra, Evta Indren, Indren Intan Susanti Simarmata Jefri Syah Putra Laoli Jorgi L.Tobing, Stefanus Juan Juanta, Palma Kumar, Sharen Lee, Brandon Lidya Silalahi Lumbantoruan, Nurima Manao, Sonatafati Manday, Dhanny Rukmana Mardi Turnip, Mardi Maria Yostin Br Tarigan Marlince N.K Nababan Marpaung, Aldo Andy Yoseph Tama Marpaung, Cantika Matthew Oullanley Lee Meri Natasia Napitupulu Mita Aprila Silpa Simanjuntak Muhammand Ridho Muliadi Marianus Sirait Musa Andrew Loyd Sitanggang Nababan, Marlince N.K Nainggolan, Winner Parluhutan Nanchy Adeliana Br S. Muham Napitupuluh, Christian Deniro Niken Sihombing Nina Purnasari Nova Riani Fransiska Novanius Lahagu Oktarino, Ade Oktoberto Perangin-angin Pamungkas, William Aldo Perangin Angin, Despaleri Perangin-angin, Despaleri Pungki Laurensius Ritonga Putra, Muhammad Amsar Rijois I. E. Saragih Rizal, Reyhan Achmad Sadarman Zebua Saljuna Hayu Rangkuti Sanjaya, Federico Saragi, Yosua Morales Saragih, Rini Hartati Sarah Simangunsong Saut Parsaoran Tamba sherly sherly Siahaan, Edivan Wasington Siahaan, Eric Simon Giovanni Sihotang, Putri Anasia Simangunsong, lamria Simanjuntak, Ester Farida Simanjuntak, Mega Herlin Simanjuntak, Ruth Marsaulina Simarmarta, Brando Benedictus Sinaga, Jasmin William Natanael Sion Putri Zalukhu Siregar, Saut Dohot Sitanggang, Maria Natalenta Siti Aisyah Siti Aisyah Sitompul, Chris Samuel Sitorus, Angelina Monica Situkkir, Miando Mangara Solly Aryza Sri Wahyu Tarigan Sri Wahyuni Tarigan Sumita Wardani Sundah, Geertruida Frederika Suyanto, Jao Han Tampubolon, Irfan Saputra Tampubolon, Johanes Joys Ronaldo Tampubolon, Tasya Rouli Christy Tarigan, Julio Putra Tarigan, Nina Veronika Tarigan, Sri Wahyuni Tifanny, Tifanny Togar Timoteus Gultom Wijaya, Bryan Wilbert Solo, Eddrick Winarti Pasaribu Yennimar Yennimar, Yennimar Yoga Tri Nugraha Yonata Laia Yumna, Farhan