Transformer has shown excellent performance in remote sensing field with long-range
modeling capabilities. Remote sensing video (RSV) moving object detection and tracking …

Decomposition is a well-known strategy in traditional multiobjective optimization. However,
the decomposition strategy was not widely employed in evolutionary multiobjective …

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

In most metaheuristic algorithms, the updating process fails to make use of information
available from individuals in previous iterations. If this useful information could be exploited …

This article investigates the properties of ratio and difference-based indicators under the
Minkovsky distance and demonstrates that a ratio-based indicator with infinite norm is the …

Dynamic multiobjective optimization problems (DMOPs) challenge multiobjective
evolutionary algorithms (MOEAs) because those problems change rapidly over time. The …

In many-objective optimization problems (MaOPs), forming sound tradeoffs between
convergence and diversity for the environmental selection of evolutionary algorithms is a …

Existing multiobjective evolutionary algorithms (MOEAs) perform well on multiobjective
optimization problems (MOPs) with regular Pareto fronts in which the Pareto optimal …

Currently, evolutionary multiobjective optimization (EMO) algorithms have been successfully
used to find a good approximation of many-objective optimization problems (MaOPs). To …

In this study, a multi-objective evolutionary algorithm based on decomposition (MOEA/D) is
proposed for energy-efficient scheduling of distributed heterogeneous welding flow shop …