A new method for improving the performance of fast local search in solving QAP for optimal exploration of state space

Quadratic assignment problems one of combinatorial optimization problems that pays to number of facilities to number of places. The objective is to minimize the cost. QAP is one of the degree of complexity of hard problems deterministic algorithms are able to solve smaller sample problem. Fast local search used to solve qap. but despite the wider space exploration. There are not certain views for better search. The objective is to provide a way to be able find a visual representation of the search space Which leads to reduced method efficiency and in cases where the distance between the points searched was a great gap as much as possible to find areas that are not searched and evaluated. The new proposed method is able to decrease average best answer fast local search algorithm from 0.65 percent to 0.26 percent and so will have a better exploration of space search. Review its performance based on standard test functions and compare it with fast local search algorithm represent quality and its advantage, provide good results in a wide range of issues permutation.