Parallel Genetic Algorithms to Solve Optimization Problems
Solving the Optimization problem efficiently is an open challenge in computer science. Most of problems in this category are hard to be solved in less time. As the problem size increases the solution becomes worse. Genetic Algorithms are used in past to get a good solution for these problems effectively. Genetic Algorithms are parallel in nature at many steps. In this paper, this parallelism of genetic algorithm is exploited and genetic algorithm is coded in two aspects, simple genetic algorithm and parallel genetic algorithm. Parallel genetic algorithm performs better on a parallel hardware, where all of the processors become busy in execution of algorithm, which leads to quick solutions.