A meta-search engine (MSE) is a system that supports unified access to multiple existing web search engines by querying them simultaneously, thereby widening coverage of the World Wide Web. Result aggregation techniques are used in an MSE to combine the results from multiple underlying web search engines and present a single consolidated result list to the user. In this paper, we propose a new method for optimization of MSE results using fuzzy analytical hierarchy process (FAHP) and modified extended ordered weighted averaging (EOWA) operator. In our method, FAHP is used for pair-wise comparison of documents in underlying search engines. We assign fuzzy importance degrees to search engines which are represented in triangular fuzzy numbers, and subsequently defuzzified using center of gravity method. Center of gravity method is found to be a better defuzzifier operator in the literature as compared to max membership method which is an important constituent of EOWA operator. The modified EOWA operator is therefore proposed to aggregate the scores of individual search engine documents so as to obtain the final ranking of the documents. Lastly, we compute the effectiveness of the proposed MSE viz. MetaSurfer by calculating the classical Precision. Since we have proposed a new method which reorders documents such that a more relevant document occupies a higher rank, therefore we have defined a new criterion to calculate effectiveness called weighted precision. The precision and weighted precision values are compared with those of existing and popular MSEs. The results show that MetaSurfer performs better than existing MSEs.