Karesel atama problemi için bulanık adaptif çaprazlamalı genetik algoritma önerisi
A Proposed Genetic Algorithm With Fuzzy Adaptive Crossover For Quadratic Assignment Problem

Summary/Abstract: The quadratic assignment problem is a type of problem that can be encountered in many different fields. The problem, which is based on the assignment of the points of activity which have flow between each other to locations with a certain distance between each other and where flow and distance has to be handled together, is very difficult to solve by classical solution methods and mostly suitable solutions can be obtained with heuristic algorithms. One of the most frequently used heuristic algorithms is Genetic Algorithm. Genetic Algorithm is a very successful method that simulates the evolution of living things with procedures involving randomness. One of the most important procedures of the algorithm is crossover. For the quadratic assignment problem, position-based crossover is often preferred in the literature. How many points will remain constant and how to determine this value is important for position based crossover. In this study, the classical Genetic Algorithm approaches, which treat the number of fixed points with predetermined values, are compared with the proposed method, fuzzy adaptive approach. By using the fuzzy adaptive approach which uses Fuzzy Logic theory which is a kind of artificial intelligence, the parameters are controlled by using the information obtained by the algorithm during the solution and the search direction of the algorithm can change more intelligently. In order to evaluate the effectiveness of the proposed method, the examples of quadratic assignment problems in the literature were utilized. With the evaluation of the results, the effectiveness of the fuzzy adaptive approach in Genetic Algorithm was revealed.

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