In recent years, the development of new algorithms for multiobjective optimization has
considerably grown. A large number of performance indicators has been introduced to …

Complexity and variety of modern multiobjective optimisation problems result in the
emergence of numerous search techniques, from traditional mathematical programming to …

Hypervolume is widely used as a performance indicator in the field of evolutionary
multiobjective optimization (EMO). It is used not only for performance evaluation of EMO …

With the advent of the Internet of Things, especially the Internet of Vehicles, abundant
environmental and mobile data can be generated continuously. A personalized …

This paper presents a new, multi-objective method of analysing and optimising the energy
processes associated with window system design in office buildings. The simultaneous …

Security is crucial for industrial wireless sensor networks (IWSNs); therefore, in this article,
we simultaneously consider the security, lifetime, and coverage issues by deploying sensor …

Fuzzy rough theory can describe real-world situations in a mathematically effective and
interpretable way, while evolutionary neural networks can be utilized to solve complex …

In the last decades, a large number of metrics has been proposed to compare the
performance of different evolutionary approaches in multi-objective optimization. This …

Neural architecture search (NAS) has emerged as a promising avenue for automatically
designing task-specific neural networks. Existing NAS approaches require one complete …

Decomposition via scalarization is a basic concept for multiobjective optimization. The
weighted sum (WS) method, a frequently used scalarizing method in decomposition-based …