Search-based software engineering (SBSE) is changing the way traditional software
engineering (SE) activities are carried out by reformulating them as optimisation problems …

This article proposes an adaptive localized decision variable analysis approach under the
decomposition-based framework to solve the large-scale multiobjective and many-objective …

Evolutionary algorithms have been shown to be very successful in solving multi-objective
optimization problems (MOPs). However, their performance often deteriorates when solving …

Internet of Things (IoT) is a huge network and establishes ubiquitous connections between
smart devices and objects. The flourishing of IoT leads to an unprecedented data explosion …

The performance of decomposition-based algorithms is sensitive to the Pareto front shapes
since their reference vectors preset in advance are not always adaptable to various problem …

The space–air–ground-integrated network (SAGIN) can enhance the performance of the
Internet of Vehicles (IoV). However, the basic hardware differences among communication …

While the industrial Internet of Things (IIoT) can support efficient control of the physical world
through large amounts of industrial data, data security has been a challenge due to various …

Both convergence and diversity are crucial to evolutionary many-objective optimization,
whereas most existing dominance relations show poor performance in balancing them, thus …

A multi-objective evolutionary algorithm based on decomposition (MOEA/D) is a classic
decomposition-based multi-objective optimization algorithm. In the standard MOEA/D …

When optimizing many-objective problems (MaOP), the same strategy might behave
differently when facing problems with different features. Therefore, obtaining problem …