Real-world Application uses of Genetic Algorithm

1. Automotive Design

Using Genetic Algorithms [GAs] to both design composite materials and aerodynamic shapes for race cars and regular means of transportation (including aviation) can return combinations of best materials and best engineering to provide faster, lighter, more fuel efficient and safer vehicles for all the things we use vehicles for. Rather than spending years in laboratories working with polymers, wind tunnels and balsa wood shapes, the processes can be done much quicker and more efficiently by computer modeling using GA searches to return a range of options human designers can then put together however they please.

2. Engineering Design

Getting the most out of a range of materials to optimize the structural and operational design of buildings, factories, machines, etc. is a rapidly expanding application of GAs. These are being created for such uses as optimizing the design of heat exchangers, robot gripping arms, satellite booms, building trusses, flywheels, turbines, and just about any other computer-assisted engineering design application. There is work to combine GAs optimizing particular aspects of engineering problems to work together, and some of these can not only solve design problems, but also project them forward to analyze weaknesses and possible point failures in the future so these can be avoided.

3. Robotics

Robotics involves human designers and engineers trying out all sorts of things in order to create useful machines that can do work for humans. Each robot’s design is dependent on the job or jobs it is intended to do, so there are many different designs out there. GAs can be programmed to search for a range of optimal designs and components for each specific use, or to return results for entirely new types of robots that can perform multiple tasks and have more general application. GA-designed robotics just might get us those nifty multi-purpose, learning robots we’ve been expecting any year now since we watched the Jetsons as kids, who will cook our meals, do our laundry and even clean the bathroom for us!

4. Evolvable Hardware

Evolvable hardware applications are electronic circuits created by GA computer models that use stochastic (statistically random) operators to evolve new configurations from old ones. As the algorithm does its thing in the running model, eventually a circuit configuration will come along that does what the designer wants. Think of reconfigurable circuits in something like a space robot. It could use a built-in GA library and simulator to re-design itself after something like radiation exposure that messes up its normal configuration, or encounters a novel situation in which it needs a function it doesn’t already have. Such GAs would enable self-adaptation and self-repair.

5. Optimized Telecommunications Routing

Do you find yourself frustrated by slow LAN performance, inconsistent internet access, a FAX machine that only sends faxes sometimes, your land line’s number of ‘ghost’ phone calls every month? Well, GAs are being developed that will allow for dynamic and anticipatory routing of circuits for telecommunications networks. These could take notice of your system’s instability and anticipate your re-routing needs. Using more than one GA circuit-search at a time, soon your interpersonal communications problems may really be all in your head rather than in your telecommunications system. Other GAs are being developed to optimize placement and routing of cell towers for best coverage and ease of switching, so your cell phone and blackberry will be thankful for GAs too.

6. Joke and Pun Generation

Among the linguistic applications of GAs – including a JAPE (automated pun generator) inspired STANDUP program to design communications strategies for people working with children who suffer communications disabilities – are GAs that search for jokes and puns. These come under the heading of “artificial creativity” and AI, but could prove very useful to class clowns and wannabe punsters whose public reputations depend upon being funnier than they actually are. These clever GAs will let you input a word you wish to pun or a subject you’d like to joke about, and will return a variety of solutions that just might lead to a lucrative career on the comedy club circuit!

7. Biomimetic Invention

Biomimicry or biomimetics is the development of technologies inspired by designs in nature. Since GAs are inspired by the mechanisms of biological evolution, it makes sense that they could be used in the process of invention as well. GAs rely primarily on something called implicit parallelism (like to like), using mutation and selection in secondary roles toward a design solution. GA programmers are working on applications that not only analyze the natural designs themselves for a return on how they work, but can also combine natural designs to create something entirely new that can have exciting applications.

So many Real-world Application uses of Genetic Algorithm, you can see full article in

Genetic algorithms and Business Intelligence

Computers have helped us to process information more efficiently and to solve problems of the real life and real businesses. The first case are the tools we use daily, software like word processors, calculator, browsers, music player, video player, email reader. In the second case, we have the software that allow us to solve recurring problems, between them we have different programing languages for different devices.

Now imagine a next phase where we have computers generating their own solutions or even computers and men working together to solve problems. It’s Genetic algorithms, and today It’s real

Nowadays, businesses are pointing to have solutions to their recurring problems and they hire expert Software developers to solve those problems. Good, excellent decision. But what happen if in any moment you need to add a new variable to the developed system? or maybe the business does not have a predictive model, and It’s changing all the time. In these cases you need to call the developer each time you need to change anything.

With Genetic algorithms It can be avoided, or optimized. If you combine technologies like grid computing, predictive modeling, data mining an genetic programming, the program you create will have the necessary to create a real intelligent business, because It knows the business and is able to create solutions each time something changes.

Businesses can use Genetic algorithms to do intelligent data analysis, sales forecasting, stock forecasting, market analysis and market prediction.

An example of the use of Genetic algorithms are “Search engines”. Advanced search engines like Google use genetic algorithms in order to analyze and classify the information around the Internet, they don’t need to know what are going to search, they just know the task Crawl, store, analyze and classify. Other examples are software created for financial trading, health care, insurance and manufacturing.

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Multigenic Genetic Expression Programming with Regulatory Gene (mgGEP-RG)

multigenic GEP dengan regulatory adalah salah satu metode terbaru dari tenik komputsi evalusioner, dibuat oleh Mwaura pada desember 2011. Dengan tujuan untuk mencari dan mengembangkan mgGEP algoritma dengan konsep mekanisme aturan-aturan (regulatory) pada gene. Seperti pada mgGEP sebelumnya, teknik ini menggunkan multiple genes dengan panjang yang sama dalam penyajian chromosome dan fungsi yang telah ditentukan sebelumnya (pre-detemined) dihubungkan oleh linking function sebagai pengendali. Dalam mgGEP-RG, fungsi-fungsi sebelumnya yang telah dihubungkan oleh linking function yang mengandung beberapa aturan pengambil keputusan untuk membuat kriteria yang memungkinkan untuk mengatur aktifasi atau menentukan gene yang digunakan pada aturan gene yang telah difungsikan sebelumnya, atau terdapatnya suatu gene baru (extra) yang menetukan gene mana yang diaktifkan dalam suatu kondisi tertentu.
Tekhnik ini lebih mendekat pada nilai biologi pada umumnya, aturan (regulatory) gene menyediakan bebeapa kondisi dari beberapa kelompok gene yang difungsikan sebelumnya untuk diaktifkan. Aturan (regulatory) gene merupakan bagian dari suatu chromosome, tetapi tidak terlibat langsung dalam kontrol suatu mekanik seperti dalam mekanik robot. Penyajian chromosome pada regulatory gene, pada umumnya sama dengan GEP lainnya, mempunyai panjang chromosome yang sama, terdapat head dan tail serta berbagai aturan dari fungsi dan terminal. Dalam implementasinya, regulatory gene ditempatkan sebagai gene pertama dalam chromosome, dapat juga ditempatkan di posisi manapun dengan beberapa aturan gene. Sebagai bagian dari chromosome, regulatory gene melakukan operasi genetik seperti pada gene lainnya.

Jika pada suatu ekperimen diketahui mengimplementasi 3 genes dengan head size, h=8, digunakan untuk membentuk mgGEP-RG chromosome, genes tersebut dihubungkan dengan IF linker sebagai output dari gene pertama untuk memutuskan kondisi dari kedua gene untuk berkespresi dan mempengruhi kinerja kendali robot. Gene pertama yang dimaksud adalah regulatory gene. Sedangkan dua gene lainnya merupakan gene pengendali aksi robot atau disebut sebagai gene structural. Pada kondisi ini, salah satu dari structural genes aktif jika keluaran (output) dari regulatory gene memenuhi salah satu dari ciri dari kedua gene struktural tersebut (dapat berupa terminal per genes), algoritma yang digunakan sebagai berikut.

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Structure Question: Adjective Clause Connector (TOEFL Skill 9)

Soal mengenai Adjective clause connector sering sekali di berikan di TOEFL Test. Silakan baca dan pelajari penjelaan berikut ini.

Perhatikan dua contoh kalimat dibawah ini:
(English Version)

1. a. This is the house (first clause)
b. I want to buy the house (second clause)

Kalau kedua clause tersebut kita gabungkan, maka menjadi: this is the house (that) I want to buy


This adalah Subject dan Is adalah Verb nya. Sedangkan Clause kedua, I adalah subject dan want adalah Verbnya. That berfungsi sebagai Connector yang menghubungkan kedua Clause diatas.

The job _____ started yesterday was rather difficult.

(A) when
(B) was
(C) after
(D) that he


– Ada dua clauses pada kalimat di atas.
– Clause pertama: Job sebagai subject dan was sebagai verb.
– Clause yang kedua: belum ada subjectnya sedangkan started sebagai verb.
– Karena ada dua clauses, juga di butuhkan Connector untuk memnghubungkan mereka.
– Jawaban terbaik adalah (D) that he karena he merupakan subject untuk kata kerja started dan connector that untuk menghubungkan kedua clause tersebut.

Perhatikan soal di bawah ini. Masing masing kalimat memiliki lebih dari satu clause. Perharikan Subject dan verb dari tiap-tiap clause dan juga connectornya. Check apakah kalimat di bawah ini benar atau salah.

1. I did not believe the story that he told me. (Correct)


First Clause : I did not believe the story
Second Clause : He told me
Adjective clause connector : that

2. Ms. Brown, whom did you recommend for the job, will start work tomorrow.(Incorrect)


First clause : Ms. Brown will start work tomorrow
Second clause : Did you recommend for the job (incorrect) It should be you recommended for the job
Adjective clause connector : whom

The correct sentence is Ms. Brown, who you recommended for the job, will start work tomorrow.

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Structure Skill: Noun clause connector/Subject ( TOEFL Skill 8)

Pada skill sebelumnya (Skill 7) A noun clause connector (whom, what dan which) hanya berfungsi sebagai connector.
(English Version)

Di skill 8 (Noun clause connector/subject), Noun Clause Connector tidak hanya berfungsi sebagai Connector tapi pada saat yang bersamaan juga berfungsi sebagai Subject.

Perhatikan contoh di bawah ini.

The company was prepared for ________ happened with the economy.

(A) it
(B) the problem
(C) what
(D) when


Kalimat diatas memiliki dua buah klausa yaitu “The company was prepared for” dan ” ……….. happened with the economy.
Klausa ke dua “…………….happened with the economy” kurang lengkap karena belum memiliki subject sekaligus connector yang berfungsi menghubungkan kedua kalimat.
Jawaban yang tepat adalah what (c) karena ini bisa berfungsi sebagai Subject dan connector.

Perhatikan soal-soal dibawah ini dan tentukan apakah kalimatnya benar (Correct) atau salah (Incorrect).

1. The teacher heard who answered the question. (C)


Kalimat pertama “The teacher heard” benar karena The teacher subject and heard verbnya. Kalimat kedua “Who answered the phoned” juga benar karena who berfungsi sebagai subject and answered sebagai verbnya. Pada saat yang bersamaan Who juga berfungsi sebagai connetor.
Jadi kalimat di atas sudah benar.

2. I do not understand it went wrong. (I)


Kalimat pertama “I do not understand” sudah benar karena I subject dan do not understand verb. Kalimat kedua “it went wrong” salah karena tidak ada connector sekaligus subject.
Kalimat yang benar seharusnya: I do not understand what went wrong.What berfungsi sebagai subject dan juga connector, sementara went nya sebagai verb,

source :

Structure Skill: Noun Clause Connector (TOEFL Skill 7)

Perhatikan contoh-contoh di bawah ini.
(English Version)

Contoh 1.

1. I don’t know (kalimat/klausa pertama)
2. Where do you live? (Kalimat/klausa kedua)

Kalau kedua kalimat/klausa diatas digabung, maka menjadi:

I don’t know where you live?

Kata kerja bantu (Auxiliary Verb) do dihilangkan

Contoh 2.

1. Can you tell me?
2. When does the bank open?

Kalau kedua kalimat diatas di gabung, maka:

Can you tell me when the bank opens?

Kata kerja bantu (Auxiliary Verb) does di hilangkan, dan verb open ditambahkan s menjadi opens.

Contoh 3.

1. Do you know?
2. What did they play last night?

Kalau digabung menjadi:

Do you know what they played last night?

Kata kerja bantu (auxiliary verb) did pada kalimat kedua di hilangkan, dan kata kerja (verb) play menjadi bentuk kedua (past tense verb) played.

Contoh 4.

1. I am not sure.

2. Where can I go to London?
What should I do for her?
How long have you studied TOEFL?
How much has she gained her weight?
Who is she?

Kalau kedua digabung, menjadi:

I am not sure where I can go to London.
I am not sure what I should do for her.
I am not sure how long you have studied TOEFL.
I am not sure how she has gained her weight.
I am not sure who she is.

Kalau WH-Questionnya menggunakan Modal (Can, Will, Would, Might, Should, etc), maka modal tersebut harus di letakan setelah kata kerja (Verb).

Kalau WH-Questionnya menggunakan To Be (am, is, are, was, were) maka To Be tersebut di letakan setelah Subject.

Kalau WH-questionnya dalam bentuk Present Perfect atau Past Perfect, maka Have, Has dan Had di letakan setelah Subject.

Itulah beberapa cara bagaimana menggabungkan dua buah kalimat/clause jika clause/kalimat yang kedua adalah wh-questions.

Hal-hal diatas harus bisa kita lakukan karena ini relevan dengan skill 7. A noun clause adalah clause/kalimat yang berfungsi sebagai NOUN. Karena Noun Clause berfungsi sebagai Noun, maka fungsinya pada kalimat bisa sebagai object of verb (object dari kata kerja) dan object of preposition (Object dari Preposisi/kata depan).

1. As Object of Verb.

Perhatikan contoh kalimat dibawah ini:

I don’t know why he said such things


Kalimat iatas memiliki dua clause/kalimat, I don’t know dan he said such things. Kedua clauses ini di gabungkan dengan connector WHY. WHY juga mengubah clause he said such things menjadi Noun Clause yang berfungsi sebagai Object of a Verb. don’t know.

2. Object of Preposition.

I am thinking about why he said such thin


Kalimat diatas memiliki dua clauses I am thinking dan he said such things. Kedua kalimat juga di hubungkandengan connector why. . WHY juga mengubah clause he said such things menjadi Noun Clause yang berfungsi sebagai Object of Preposition about.

Berikut ini adalah contoh soal bagaimana adverb clause connector digunakan:


The citizens worry about ____ is doing.

(A) what the government
(B) the government
(C) what
(D) what the government it

Source :

Structure Skills: Adverb Clause Connector ( TOEFL Skill 6)

Perhatikan dua contoh kalimat di bawah ini:
(English version)
He is tired because he has been working so hard.
Because he has been working so hard, he is tired.


Di masing-masing contoh kalimat di atas terdapat dua buah klausa/kalimat:

He is tired
He has been working hard

Kedua klausa/kalimat diatas tentunya membutuhkan connector untuk menyambungkan mereka dan mempunyai arti. Connector yang tepat adalah because. Sehingga kalimatnya menjadi

He is tired because He has been working hard, or
Because he has been working hard, he is tired.

Kalau Connectornya berada di tengah-tengah, maka tidak membutuhkan koma tapi kalau connectornya ada di awal kalimat, maka di butuhkan koma.

Contoh dibawah ini menunjukan bagaimana Adverb Clause Connector biasa di tes di Structure Section dari TOEFL test.


_____ arrived at the library, he started to work immediately.

(A) The student
(B) When
(C) He
(D) After the student


Dari dua klausa/kalimat diatas, kalimat pertama “…..arrive at the library” belum memiliki Subject tapi sudah memiliki Verb. Sedangkan kalimat kedua sudah memiliki Subject, he, dan Verb, started.
Tidak juga ada juga Connector untuk menghubungkan kedua kalimat tersebut.
Jawaban terbaik adalah (D) karena ada subject, the student, untuk melengkapi kalimat arrive, dan connector, when, untuk menghubungkan kedua kalimat tersebut.


Perhatikan soal-soal dibawah ini dan tentukan apakah kalimatnya bennar (Correct) atau salah (Incorrect)

1. After the plane circled the airport, it landed on the main runway. (C)


Kedua kalimat diatas sudah memiliki subject dan verb.
Connector “when” juga benar dan bisa menghubungkan kedua kalimat diatas.

2. The registration process took many hours since the lines so long. (I)


Kalimat kedua memiliki subject, the lines, tapi tidak memiliki verb. Kalimat yang benar untuk kalimat kedua adalah The lines were so long.
Connector “since” juga benar dan bisa menghubungkan kedua kalimat diatas.

3. This type of medicine can be helpful, it can also have some bad side effects. (I)


Kedua kalimat diatas benar, tapi belum ada Connectornya.
Connector yang benar mungkin BUT. Jadi kalimat lengkapnya adalah ……….can be helpful, BUT it can also have…………………

4. The waves were amazingly high when the storm hit the coastal town. (C)


Kedua kalimat diatas sudah benar begitu juga dengan connectornya.

5. We need to get a new car whether is on sale or not. (I)


kalimat kedua tidak memiliki Subject. Seharusnya It is on sale or not.
Connector “whether” juga benar dan bisa menghubungkan kedua kalimat diatas.

source :


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