Bayesian optimisation is a statistical method that efficiently models and optimises expensive
“black-box” functions. This review considers the application of Bayesian optimisation to …

This paper provides a comprehensive survey of the most popular constraint-handling
techniques currently used with evolutionary algorithms. We review approaches that go from …

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

Complex continuous optimization problems widely exist nowadays due to the fast
development of the economy and society. Moreover, the technologies like Internet of things …

Constrained multiobjective optimization problems (CMOPs) involve multiple objectives to be
optimized and various constraints to be satisfied, which challenges the evolutionary …

Real-world optimization problems have been comparatively difficult to solve due to the
complex nature of the objective function with a substantial number of constraints. To deal …

Resource allocation plays a pivotal role in improving the performance of wireless and
communication networks. However, the optimization of resource allocation is typically …

Abstract Background: The Chimp Optimization Algorithm (ChOA) is a hunting-based model
and can be utilized as a set of optimization rules to tackle optimization problems. Due to …

When solving constrained multiobjective optimization problems (CMOPs), the utilization of
infeasible solutions significantly affects algorithm's performance because they not only …

This study develops net-zero energy management and optimization approaches for the
commercial building sector in cities powered by renewable energy systems integrated with …