Genetic Algorithm for Solving Constrained Optimization Problem
Ximing Liang, Haoyu Qin, Wen Long · Jisuanji gongcheng · 2010
A genetic algorithm to handle constrained optimization problem is proposed.This method searches the decision space of a problem through the arithmetic crossover of feasible and infeasible solutions,and performs a selection on feasible and infeasible populations respectively according to fitness and constraint violation.It uses the boundary mutation on feasible solutions and the non-uniform mutation on infeasible solutions because the solutions usually deviate from the constraint domain after the traditional mutation operation.It maintains the population diversity through dimension mutation.Numerical results show that it is an effective algorithm.