Distributed Genetic Algorithm
Using Artificial intelligence our main purpose to find the best fit population for this purpose we will use genetic algorithms .First,a pool of random potential solutions is created that should have adequate diversity.Preprocessing population of GA. Next,The fitness of each member is
Project Title
Distributed Genetic Algorithm
Project Area of Specialization
Project Summary
Using Artificial intelligence our main purpose to find the best fit population for this purpose we will use genetic algorithms
.First,a pool of random potential solutions is created that should have adequate diversity.Preprocessing population of GA.
Next,The fitness of each member is computed.Selection on the basis of fitness
Next,Members of the population are selected based on some algorithm.The two simplest approaches are roulete wheel selection, and elitist selection.
The next step is to recombine these members material to form the members of the next population.
Project Objectives
to find different ways :-
1-computation
2-implementation
3-strategies
4-optimization method
5-best fit population
Project Implementation Method
Scala in context of spark while results will be evaluated on cluster.
Benefits of the Project
We can find a différent way to solve optimization problems.
Technical Details of Final Deliverable
Being population based characteristics of GA it would solve evolutionary problems
Final Deliverable of the Project
Type of Industry
Technologies
Sustainable Development Goals
Required Resources
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Data Bricks Analytics Server Services | Equipment | 1 | 70000 | 70000 |
| Total in (Rs) | 70000 |
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