A complex-genetic algorithm for solving constrained optimization problems

Constrained optimization problems(COPs) are a kind of mathematic programming problem frequently encountered in the disciplines of science and engineering application. After analyzing weaknesses of existing constrained optimization evolutionary algorithms (COEAs), a novel improved algorithm called Complex-GA, which converts COPs into Multi-objective optimization problems(MOPs) and effectively combines Multi-objective optimization concept with global and local search, was proposed to handle COPs. Complex-GA increases the speed of optima search noticeably by combining the advantages of the two methods and overcomes the disadvantages of them.