Metasearch Engine

1. User submits a query to the metasearch engine interface.
2. The query submitted is processed to remove irrelevant words, stopwords, etc.
3. The refined query is sent to the search engines - Google, Bing
4. The underlying search engines accesses the network resources and then return back their respective results to Meta Search Engine.
5. Meta Search Engine aggregates the returned results into single consolidated rank list by using genetic algorithm.

Genetic Algorithm : 

Initialze Population : n*m
	n is number of search engines
	m is the maximum number of documents returned 

To calculate fitness function
1. Assign weights to documents ( top most document in each search engine’s result list gets highest value)
	doc score of a search engine, i = total no of documents returned by the search engine, i - position + 1
2. Individual search engines are also assigned weights 
	w of i = (i/n)^alpha - (i-1/n)^alpha , alpha is a random no (0,1) n is the no of search engines
3. Calculate OWA(Ordered Weighted Average) operator of document of i = (w of i * doc score of document j)
4. Calculate Average(OWA) of i = sum (OWA of all documents of i)/Total no of documents returned by search engine, i
5. Fitness(i)= (Avg(OWA)-CP/maxfit-CP) ; if (beta * CP)>fitness(i) then fitness(i)=maxfit
	maxfit=max of Avg(OWA);beta is a random no (0,1);CP - cut point=0.5*maxfit

Apply genetic operators : mutation, crossover, selection

The documents are ranked in decreasing order of their fitness value i.e. most relevant document have higher fitness value and is present at top position in rank list.

Finally the duplicates are removed and result is displayed to user.