Deriving Fitness Function for GA search technique

This project aims to derive the fitness function for a group of 4 different case studies. Every case study covers a specific application. However, all case studies are composed of sequences of events and every event modifies the system’s state. For instance, add(x).add(x).front() is a sequence of events for circular queue; it generates 2 different states: (len=1; rear=0; front=0) and (len=2; rear=1; front=0). The last event (i.e. front) is only for printing the queue’s front, so it can be neglected as it does not modify the state. The events that modify the data states, called sensitive, and the ones that do not modify the states, called insensitive, are specified in the attached file. As well, the data to be used is attached.

The fitness function has to feature minimizing the number of sequences in the population along with saving sequences with unique states. Hence, there are 2 types of redundancies: redundant sequence (i.e. duplicate sequences or sequence is subset from another) and redundant states in the sequence (i.e. such as adding to full queue or removing from empty queue). Besides, the fitness function has to be applicable for all case studies. It is worth to note that we are targeting more than one solution, not only the best one.

So, any interested who is good in math and genetic algorithm please contact me.

Taidot: Geenitekniikka, Matlab ja Mathematica

Näytä lisää: types of algorithm, study algorithm, search algorithm in c, queue algorithm in c, number function, function number, feature of algorithm, e-circular, e circular, different types of algorithm, best search algorithm, a search algorithm, algorithm study, algorithm function, algorithm for search, 2 63 1, binary search tree insert function, search replace program function calls main, search function website, search function java, search function asp html, add search function jsp, search function access, microsoft access search function code, microsoft access search function

Tietoa työnantajasta:
( 1 arvostelu ) Kedah, Malaysia

Projektin tunnus: #8654708

5 freelanceria on tarjonnut keskimäärin %project_bid_stats_avg_sub_26% %project_currencyDetails_sign_sub_27% tähän työhön


I'm a PhD student in Engineering with a Master's in Statistics. Expert in Matlab, Econometric and statistical modeling of pretty much everything you can think of. These include expertise on protocol development, resear Lisää

RM526 MYR 9 päivässä
(5 arvostelua)

Hi I have done my doctorate in the area of evolutionary algorithm. I am ready to do this . I have very good profile on I have executed more than 20 projects on I am looking forward Lisää

RM222 MYR 3 päivässä
(13 arvostelua)

Hi, I am an expert in Matlab. I have much experience in Deriving Fitness Function for GA search technique. I can do it correctly. Regards.

RM777 MYR 3 päivässä
(6 arvostelua)

I am an expert in this field from long time. I can do it perfectly. I’ll be waiting for your positive reply thanks.

RM486 MYR 3 päivässä
(3 arvostelua)

I am Senior in computer science with 10 years expertise, with proficiency in software development . Following are my area of expertise - servers, linux, vmware, windows - System / Windows / Desktop application develo Lisää

RM1000 MYR 3 päivässä
(0 arvostelua)

Hi, I'm an expert and experienced developer in Genetic Algorithm. I'll be developing the code in Python. Please get in touch for discussing further details. Thanks.

RM700 MYR 3 päivässä
(0 arvostelua)

i hold MSc in electrical engineering.i expert on matlab. i think i can do this job at the best at minimum time.

RM513 MYR 7 päivässä
(0 arvostelua)

A proposal has not yet been provided

RM555 MYR 5 päivässä
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