Tutorial : Introduction to Genetic Algorithm n application on Traveling Sales Man Problem (TSP)

[@harshbari1510]

Taught better than IIT Professor, really very great video. Thank You

[@gopalprasadmalakar12]

Thanks a ton for your feedback @harshbari1501

[@codexhammered007]

AMAZING!!! BEST explanation that one can find on the internet!

[@husein_alfil]

Hello ! Thank you very much for this great video !! Your Videos and explanation are really unique and better than most Videos on KZbin. I see a huge potential for your channel to grow and help millions of programmers around the world so I hop that you keep doing those great videos about programming.

[@aniket799]

That crossover part and mutation part was really helpful. Thanks. Appreciate it.

[@RicardoTetti]

This video saved me. Thanks, Mr. Malakar

[@ns3lover779]

what's amazing presentation , thank you coach.

[@bradytony3272]

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[@rickydariel2018]

@Brady Tony Instablaster :)

[@bradytony3272]

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[@rickydariel2018]

@Brady Tony no problem :D

[@yashasvimahajan2298]

Amazing Explanation Sir !!

[@movie4dilip]

Excellent explanation and the content is good

[@brunoyamashita5964]

Amazing explanation! Thx so much!

[@anantshekhar698]

What is the guarantee that we will get the correct output at the end of threshold number of iterations?

[@tibebualene7943]

A very good explanation. how can i use in flow shop scheduling problem?

[@ifrahabdirahman1315]

Thank u best explanation with good example

[@prayaggore4392]

There is always an Indian guy on Yotube who explains it better. How? Great job though....Thanks

[@asheeshmathur]

Wonderful explanation, do you have a c++ code to illustrate this algorithm.

[@geraldmacias7037]

thanks you saved my semester

[@cuteyo4372]

Excellent explanation !!

[@theWorldOfIss]

How to implement in multiple traveling salesman problem using NSGA-2.

[@dejandozet]

I was looking for a simple and understandable explanation and this is it! 🙂. Do you have one for the VRP?

[@yasirnaeem7192]

have you found anything on VRP

[@sravanchilumula5213]

One doubt: in this what type of cross over you used

[@debolinakundu7687]

How to get the random number for selecting the chromosome?

[@doditsuprianto6474]

excellent presentation. good job

[@TheHpsh]

personly I think it really a mistake to use crossover here, feel it just create too much noise, and we really should rather test new combination many times, and bacterias don't do crossovers. also, as I see it, a city here would be more like basepair, and basepair is not mixed, only genes, and genes are in most situation complete solutions

[@sofiapoobalan4985]

Sir nice explanation but what is thefinal solution

[@josecarlosferreira4942]

Thank you sir!

[@konkavinod5078]

nice explanation

[@zoeyxster]

The presentation doesn't tell us which the is fittest?

[@sanyammaheshwari7575]

Hi I am working on formation of a mathematical model of a single route BUS Transit System for making a optimal timetable to cover entire demand as well as minimum frequency to cover it. In order to it I went through various research papers. Firstly I starting with the help of AMPL Software. But it caused me difficulty in finding optimal frequency because for its calculation it is a series of events. In AMPL it is easy to solve using LPP. I have been through various research papers it stated use of Genetic Algorithm. If possible I need your assistance in this so that I can formulate a mathematical model of Bus Transit System.

[@teamextgaming2001]

Thank you sir

[@roshnipradhan5140]

how can i apply it in task scheduling

[@nmana9759]

9:19 Why 50 chromosomes are chosen out of 100? Where does the 100 come from?

[@gopalprasadmalakar12]

50 out of 100 is a way of selecting best solutions for next iteration. One create first set of chromosomes randomly and keep evolving based on best set of chromosomes.

[@AbhishekVerma-kj9hd]

How to find random number

[@jessiebenson777]

well-done

[@cuteyo4372]

How to do floating point mutation?

[@ramupenki]

Respected Sir, Please tell me how to do linear inequality eqns optimization based on genetic algorithm

[@tanishkanarayan1210]

For constrained GA optimisation you can also use GA toolbox available in MATLAB. It very easy to use and saves time of writing a code from the scratch.

[@lipsachhotray1021]

One doubt! is it always necessary that at the end of every run of the algorithm we will get better and better values? Is it possible that we can by any chance get not so satisfactory fitness value at the end of one iteration?

[@TheHpsh]

I would say it depends on the algorithm, I have made an algorithm where "agents" are getting shorter and shorter "time" to they reproduce, and just randomly kill agents so the population is stable, it will still work over time, but even the best mutation can be killed, but it is very slow, since I am pretty bad at programming

[@TheHpsh]

​ Venom Snake well, personly I would think you already know much more than me, I never even get into Java. and At my age, it is a bit hard to get into. personly I use a language called LiveCode, but think it would be better to go for something like python or javascript

[@kaushambichandel8185]

May I get this ppt please

[@irfanleghari677]

Good 1