An evolutionary algorithm of contracting search space based on partial ordering relation for constrained optimization problems

A new evolutionary algorithm, which can contract search space based on the partial ordering relation and is designed to solve nonlinear programming (NLP), is proposed in this paper. Firstly, the partial ordering relation is used for evaluating an individual, which ensures that individual competition is more impartial. Secondly, by taking advantage of incomplete evolution, which provides good individuals in short time, we can locate regions of optimal solutions and contract the search space and thus reduce the search space and increase the convergence rate. Thirdly, we prove that the algorithm can find optimal solutions. Finally, the algorithm can be easily parallelized. Numerical experiments demonstrate that our techniques are superior to other methods in terms of solution quality and robustness.