Solve Simple Linear Equation using Evolutionary Algorithm
Lubna Zaghlul Bashir · World Scientific News · 2015
Modern programs present a large number of optimization options covering the many alternatives to achieving high performance for different kinds of applications and workloads. Selecting the optimal set of optimization options for a given application and workload becomes a real issue since optimization options do not necessarily improve performance when combined with other options. In this work we use genetic algorithms to solve linear equation problem. Suppose there is equality a + 2 b + 3 c = 10, genetic algorithm will be used to find the value of a, b and c that satisfy the above equation. Genetic algorithms are stochastic search techniques that guide a population of solutions towards an optimum using the principles of evolution and natural genetics. In recent years, genetic algorithms have become a popular optimization tool for many areas of research, including the field of system control, control design, science and engineering. Results shows that many practical optimization problems require the specification of a control function, and The GA does find near optimal results quickly after searching a small portion of the search space.