A Decade of Productive FPGA Utilization With Genetic Algorithms
Genetic algorithms are one of the best ways to deal with the optimization problems. They are precisely suitable for mixed combinatorial problems. As genetic algorithms find the solution by producing more number of population generations based on selection, crossover, mutation etc., it can be further improved by exploiting computation power of Field programmable gate arrays. The FPGAs are highly used reconfigurable hardware, which increase the speed of genetic algorithms. In this paper, the exploitation of FPGA to implement genetic algorithm based optimization problems in different frontiers for the past decade is studied.