μJADEε: Micro adaptive differential evolution to solve constrained optimization problems
Aldo Márquez-Grajales, Efrén Mezura‐Montes · 2016
A highly competitive micro evolutionary algorithm to solve unconstrained optimization problems called μJADE (micro adaptive differential evolution), is adapted to deal with constrained search spaces. Two constraint-handling techniques (the feasibility rules and the ε-constrained method) are tested in μJADE and their performance is analyzed. The most competitive version is then compared against two highly-competitive algorithms for constrained optimization when solving a well-known set of 36 test problems, and also against a small population algorithm tested on another well-known set of thirteen problems. The results show that μJADE provides a better performance when coupled with the ε-constrained method and also that its results are competitive against those provided by state-of-the-art approaches.