Constraint Handling in Multi-Objective Optimization


Multi-objective evolutionary algorithms (MOEAs) have been intensively studied and successfully applied to many engineering problems. Since most real-world application problems involve constraint conditions as well as multiple objectives, evolutionary algorithms are requested to efficiently and effectively handle constraint conditions and multiple objectives simultaneously. This leads to several proposals of constraint handling methods for MOEAs. For example, some constraint handling methods utilize constraint violations in addition to objective values for the ranking of feasible and infeasible solutions in the current population. Other constraint-handling methods are based on repair procedures to generate feasible solutions from infeasible ones. Several ideas have been proposed to efficiently utilize infeasible solutions to drive the multiobjective search to promising regions in the search space and/or to escape from local optima. Constraint-handling methods often have a dominant effect on the search performance of MOEAs in constrained multi-objective optimization problems.

Over the past two decades, a considerable number of studies have been conducted on MOEAs. However, the number of studies about constraint-handling in MOEAs is still not enough. To fully develop a potential utility of evolutionary multi-objective optimization, this special session focuses on constraint-handling especially in evolutionary multi-objective optimization.


  • Algorithm design for constraint handling in evolutionary multiobjective optimization such as
    • Penalty function design
    • Ranking of feasible and infeasible solutions
    • Solution representation for constraint handling
    • Utilization of infeasible solutions
    • Repair operators
    • Separation of constraints and objectives
    • Integration of constraints and objectives
    • Hybridization of different techniques
  • Benchmark problem design for constrained multiobjective optimization
  • Real-World Applications of constrained multiobjective optimization

Paper Submission

Special session papers are treated the same as regular papers and must be submitted via the CEC 2015 submission website. When submitting choose the "Constraint Handling in Multi-Objective Optimization" special session from the "Main Research Topic" list.


  • Minami Miyakawa, The University of Electro-Communications, Japan
  • Carlos Artemio Coello Coello, CINVESTAV-IPN, Mexico
  • Kalyanmoy Deb, Michigan State University, USA
  • Hisao Ishibuchi, Osaka Prefecture University, Japan

Contact Information

E-mail: miyakawa [at] hs.hc.uec.ac.jp (Minami Miyakawa)

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Last-modified: 2015-06-02 (Tue) 00:32:37 (2301d)