Metaheuristic algorithms are highly popular in the field of optimization because of their
gradient-free nature and strong applicability. Grey Wolf Optimizer (GWO for short) performs …

As the scale of modern power systems gradually increases, the optimization effect and
computational efficiency of the traditional centralized economic dispatching method can no …

Most of the industrial design problems have non-linear constraints, high computational cost,
non-convex, complicated, and large number of solution spaces. This poses a challenge for …

Compared to unconstrained global optimization, constrained optimization problems (COPs)
introduce extra complexity to the search space due to constraints, making the issues more …

Constrained multiobjective optimization problems (CMOPs) typically present numerous local
optima, which can be deceptive. Current constrained multiobjective algorithms (CMOEAs) …

With the advancement of information technology, the concept of local-edge-cloud computing
has gained prominence. Operating on a collaborative model, heterogeneous computing …

Abstract The Internet of Things (IoT) is an emerging technology, increasingly integrated into
diverse everyday devices. It promises to enhance human lives by improving accessibility of …

Constrained multiobjective problems are commonly encountered in real-world optimization
scenarios, often presenting significant challenges due to the complex nature of the feasible …