A Coevolutionary Algorithm Based on ε-Constraint and Augmented Lagrangian Methods
Minqiang Li · Systems engineering and electronics · 2002
This paper introduces a coevolutionary method developed for solving multiobjective optimization problems. First thee-constraint method is adopted to transform a multiobjective optimization problem into a constrained optimization problem. Second the augmented Lagrangian method is taken to transform the constrained optimization problem into a zero-sum game with the saddle-point solution. At last, based on the concept of the coevolution, two populations are used to present the two players and solve the equilibrium point. Selection, recombination and mutation are done by using the evolutionary mechanism of simple genetic algorithm (SGA). Some benchmark problems are solved, which demonstrates that the method introduced here is better than other similar evolutionary algorithms in accuracy and stabilization.