1. Home
  2. Lainnya

Genetic Algorithms Diagnostic System for an Airline

29

18.7 Genetic Algorithms

 Goal evolutionary algorithms: Demonstrate Self-organization and A daptation by Exposure to the Environment  System learns to adapt to changes.  Example 1: Vector Game – Random Trial and Error – Genetic Algorithm Solution  Process Figure 18.11  Example: The Game of MasterMind Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ 30 Definition and Process Genetic algorithm : an iterative procedure maintaining a population of structures that are candidate solutions to specific domain challenges Grefenstette [1982]  Each candidate solution is called a chromosome  Chromosomes can copy themselves, mate, mutate  Use specific genetic operators - reproduction, crossover and mutation. Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ 31 Most Genetic Algorithms  Reproduction  Crossover  Mutation Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ 32 Applications and Software  Type of machine learning  Set of efficient, domain- independent search heuristics for a broad spectrum of applications 33 Genetic Algorithm Applications  Dynamic process control  Induction of rule optimization  Discovering new connectivity topologies  Simulating biological models of behavior and evolution  Complex design of engineering structures  Pattern recognition  Scheduling  Transportation  Layout and circuit design  Telecommunication  Graphs Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ 34 Applications  Channel 4 Television England to schedule commercials  Driver scheduling in a public transportation system  Jobshop scheduling  Assignment of destinations to sources  Trading stocks  Productivity in whisky making is increased  Often Genetic Algorithm hybrids with other AI methods Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ 35 Packages  Evolver Excel spreadsheet addin  OOGA object-oriented GA for industrial use  XperRule Genasys ES shell with an embedded genetic algorithm Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ 36

18.8 Optimization Algorithms

Dokumen yang terkait

ANALISIS KEMAMPUAN MENYELESAIKAN SOAL PISA DITINJAU DARI ASPEK LOGIKA DAN PENALARAN PADA SISWA USIA 15 TAHUN DI MTS NEGERI JEMBER 1

4 99 55

REPRESENTASI NILAI – NILAI KEPAHLAWANAN (Analisis Semiotik Pada Film Tragedi Jakarta 1998 Karya Tino Saroengallo)

0 17 1

KOMUNIKASI POLITIK IMAM KABUL DALAM RUBRIK MIMBAR JUM’AT Sebuah Analisis Wasana Pada Rubrik Mimbar Jum’at di Koran Harian Malang Post edisi 8, 15 Juni dan 6, 13 Juli 2007)

0 27 2

Efisiensi Biaya Usahatani Tebu Rakyat Mandiri (TRM) di Kecamatan Tulungagung Kabupaten Sidoarjo Masa Tanam 1997 - 1998

0 25 45

Hubungan komunikasi guru-siswa dengan prestasi belajar siswa pada mata pelajaran IPS di MAN 15 Jakarta

2 46 130

Pengaruh Metode Pembelajaran Learning Starts With A Question (LSQ) Terhadap Hasil Belajar Mata Pelajaran IPS Kelas IV Di MIN 15 Bintaro

4 49 215

Tinjauan Hukum Terhadap Kemiripan Merek Pada Produk Makanan Dan Minuman Dihubungkan Dengan Undang-Undang Nomor 15 Tahun 2001 Tentang Merek

4 81 87

Perilaku Komunikasi Pelatih Dengan Murid Dalam Program Pendidikan Seni tari (Studi Deksriptif Mengenai perilaku Komunikasi Pelatih Dengan Murid Dalam program Pendidikan Seni Tari Di Sanggar Bali Githa Saraswati Jl. Dr. Otten No. 15 Bandung)

0 11 1

BUKU SAKU edit 15 Feb1

0 23 35

PENGARUH KETERLIBATAN SISWA DALAM ORGANISASI EKSTRAKURIKULER TERHADAP BUDI PEKERTI SISWA SMA NEGERI 15 BANDAR LAMPUNG TAHUN PELAJARAN 2012/2013

12 145 86