Blended Ranking to Cross Infeasible Regions in ConstrainedMultiobjective Problems

We present a multiobjective evolutionary algorithm designed to reliably cross infeasible regions of objective space and find the true constrained Pareto front, which may lie across multiple disconnected feasible regions. By blending an individual's rank in objective space with its rank in constraint space, some infeasible solutions may be selected over some feasible solutions, allowing the population to traverse infeasible regions smoothly. Results from artificial benchmark problems qualitatively illustrate this behaviour, in contrast to NSGA-II which must cross infeasible regions in a single generation

[1]  Carlos A. Coello Coello,et al.  An updated survey of GA-based multiobjective optimization techniques , 2000, CSUR.

[2]  José L. Verdegay,et al.  Evolutionary Techniques for Constrained Optimization Problems , 1999 .

[3]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[4]  K. C. Seow,et al.  MULTIOBJECTIVE DESIGN OPTIMIZATION BY AN EVOLUTIONARY ALGORITHM , 2001 .

[5]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[6]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[7]  Joshua D. Knowles,et al.  Bounded archiving using the lebesgue measure , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[8]  Kalyanmoy Deb,et al.  Constrained Test Problems for Multi-objective Evolutionary Optimization , 2001, EMO.

[9]  Andres Angantyr,et al.  Constrained optimization based on a multiobjective evolutionary algorithm , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[10]  Carlos Artemio Coello-Coello,et al.  Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art , 2002 .

[11]  Kalyanmoy Deb,et al.  A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II , 2000, PPSN.

[12]  S. Ranji Ranjithan,et al.  Constraint Method-Based Evolutionary Algorithm (CMEA) for Multiobjective Optimization , 2001, EMO.