Handling constrained multiobjective optimization problems (CMOPs) is extremely
challenging, since multiple conflicting objectives subject to various constraints require to be …

This paper presents a review of emerging techniques for enhancing the practical application
of city logistics models. A number of models have been applied to practical problems for …

In cardiac electrophysiology, there exist many sources of inter-and intra-personal variability.
These include variability in conditions and environment, and genotypic and molecular …

This article presents a new constraint-handling technique (CHT), called shift-based penalty
(ShiP), for solving constrained multiobjective optimization problems. In ShiP, infeasible …

Various real-world problems can be attributed to constrained multiobjective optimization
problems (CMOPs). Although there are various solution methods, it is still very challenging …

Among the constraint-handling techniques (CHTs) in constrained multiobjective
optimization, constrained dominance principle (CDP) is simple, flexible, nonparametric, and …

Dynamic constrained multiobjective optimization problems (DCMOPs) abound in real-world
applications and gain increasing attention in the evolutionary computation community. To …

Real life optimization problems often involve one or more constraints and in most cases, the
optimal solutions to such problems lie on constraint boundaries. The performance of an …

Highly constrained multiobjective optimization problems (HCMOPs) refer to constrained
multiobjective optimization problems (CMOPs) with complex constraints and small feasible …

The core task of constrained multiobjective optimization is to achieve a tradeoff between
exploration and exploitation as well as a tradeoff between constraints and objectives. We …