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ITS » Inauguration Speech » Teknik Industri Posted by setiawan04@its.ac.id at 09/01/2012 12:41:35 • 111 Views
METAHEURISTIK: DARI OPTIMASI KE DATA MINING
METAHEURISTIK: FROM OPTIMIZATION TO DATA MINING
Created by :
BUDI SANTOSA ( 196905121994021001 )
| Subject: | Optimasi | | Alt. Subject : | Optimization | | Keyword: | optimasi linier programing simplex non linear |
[ Description ]
Jaman batu berakhir bukan karena ketersediaan batu habis, namun karena munculnya alternatif-alternatif baru dalam pembuatan perkakas dan peralatan.Jaman batu adalah salah satu masa penting dalam sejarah kehidupan di muka bumi. Jaman batu tetap berkontribusi sebagai mata rantai perkembangan alat-alat pertukangan atau perkakas dalam kehidupan manusia sehingga mencapai level seperti sekarang. Begitu juga dalam perkembangan ilmu optimasi.Temuan para ahli di masa lalu, sampai kini masih tetap memberi kontribusi penting.Sebagai contoh temuan-temuan Isaac Newton (1643-1727) atau Augustin-LouisCauchy (1789-1857) di dalam bidang matematika sekitar 200 tahun yang lalu,ternyata sampai sekarang masih banyak dipakai dalam rangka mencari solusi
permasalahan optimasi yang dihadapi. Bahkan algoritma baru dalam optimasi seperti interior point method yang dipelopori Karmarkar pada 1984 masih mempergunakan teknik steepest descent yang ditemukan Cauchy. Seperti kita ketahui, dunia optimasi pernah dilanda kegemparan ketika Narendra Kamarkar mengajukan teknik baru interior point method(IPM) sebagai alternatif dari algoritma simplex dalam penyelesian linear programming. Bahkan ia mengklaim IPM lebih baik dari simplex untuk problem berukuran besar. )ika simplex bergerak dari satu titik ektrim ke titik ekstrim lain dalam proses menemukan solusi optimal dari linear programming, maka IPM berusaha memulai iterasi
dari titik di dalam feasible region (interior point) menuju ke titik optimal dengan menggunakan arah dari negative gradient (gradient descent) . Algoritma Simplex, temuan George Dantzig dan Kantorovich hampir 40 tahun sebelumnya untuk pertama kalinya mendapatkan 'tantangan' berarti. IPM kemudian diperluas penggunaannya untuk permasalahan nonlinear programming. Teknik yang diajukan oleh Kamarkar diklaim sebagai ekuivalen dengan projected Newton barrier method oleh Phillips Gill. Temuan masa lalu masih menginspirasi manusia modern. Walaupun orang mulai menemukan dan mencari metode atau algoritma baru yang lebih baik untuk tujuan pemecahan masalah ini, namun temuan Newton atau Cauchy dalam mencari solusi fungsi nonlinear telah memberi sumbangan besar dalam bidang optimasi
Alt. Description
Stone Age ended not because of the availability of the stone out, but due to the emergence of new alternatives in the manufacture of stone tools and peralatan.Jaman is one important period in the history of life on earth. Stone age still contribute the development chain and carpentry tools or tools in human life so as to achieve the level as now. So also in the development of science optimasi.Temuan experts in the past, until now still remains to contribute penting.Sebagai example the findings of Isaac Newton (1643-1727) or Augustin-LouisCauchy (1789-1857) in the field of mathematics about 200 years ago, it is still widely used in order to find the solution of optimization problems encountered. Even the new algorithm in optimization such as interior point methods pioneered Karmarkar in 1984 are still using steepest descent techniques are found to Cauchy. As we know, the world is optimization never hit a stir when it proposed a novel technique Narendra Kamarkar interior point method (IPM) as an alternative to the simplex algorithm in linear programming penyelesian. In fact he claimed HDI better than simplex for large problems. ) Ika simplex moves from one extreme point to another extreme point in the process of finding an optimal solution of linear programming, then try to start the iteration of IPM points inside the feasible region (interior point) toward the optimum point by using the direction of negative gradient (gradient descent) . Simplex algorithm, the findings of George Dantzig and Kantorovich nearly 40 years earlier for the first time get a 'challenge' means. IPM then extended to nonlinear programming problems. The technique proposed by Kamarkar claimed to be equivalent to the projected Newton barrier method by Gill Phillips. The findings of the past still inspire modern humans. Although people began to discover and find new methods or algorithms are better for the purpose of solving this problem, but the findings of Newton or Cauchy in finding solutions to the nonlinear function has contributed greatly in the field of optimization
| Date Create | : | 09/01/2012 | | Type | : | Text | | Format | : | pdf | | Language | : | Indonesian | | Identifier | : | ITS-Pidato-3100012000000 | | Collection ID | : | 3100012000000 | | Call Number | : | ITS 620 Bud m |
Source : Pidato, ITS 620 Bud m, 2012
Coverage : ITS Community
Rights : Copyright @2012 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library
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