Investigating Constraint Relationship in Evolutionary Many-Constraint Optimization
This work addresses the challenge of managing extensive constraints in optimization for researchers and practitioners in evolutionary computation, but it appears incremental as it builds on existing constraint handling methods.
The paper tackles the problem of handling many constraints in evolutionary optimization by analyzing pairwise constraint relationships (conflicting, harmonious, independent) to simplify many-constraint optimization problems, with methods proposed for identifying these relationships and discussing their transitivity.
This paper contributes to the treatment of extensive constraints in evolutionary many-constraint optimization through consideration of the relationships between pair-wise constraints. In a conflicting relationship, the functional value of one constraint increases as the value in another constraint decreases. In a harmonious relationship, the improvement in one constraint is rewarded with simultaneous improvement in the other constraint. In an independent relationship, the adjustment to one constraint never affects the adjustment to the other. Based on the different features, methods for identifying constraint relationships are discussed, helping to simplify many-constraint optimization problems (MCOPs). Additionally, the transitivity of the relationships is further discussed at the aim of determining the relationship in a new pair of constraints.