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

The bias feature is a major factor that makes a multiobjective optimization problem (MOP)
difficult for multiobjective evolutionary algorithms (MOEAs). To deal with this problem …

Evolution strategies are a class of evolutionary algorithms for black-box optimization and
achieve state-of-the-art performance on many benchmarks and real-world applications …

The collaborative task assignment involved in Command and Control Systems is a key
problem to be solved. The existing researches have their limitations to the natures of …

This paper integrates an estimation of distribution (EoD)-based update operator into
decomposition-based multiobjective evolutionary algorithms for binary optimization. The …

Decomposition has been the mainstream approach in the classic mathematical
programming for multi-objective optimization and multi-criterion decision-making. However …

In command of modern intelligent operations, in addition to solving the problem of multi-unit
coordinated task assignment, it is also necessary to obtain a suitable plan according to the …

This study introduces a novel multi-objective cooperation search algorithm based on
decomposition (MOCSA/D) to address multi-objective competitive challenges in engineering …

A multi-objective evolutionary algorithm based on decomposition (MOEA/D) serves as a
robust framework for addressing multi-objective optimization problems (MOPs). However, it …

In the last two decades, multiobjective optimization has become mainstream because of its
wide applicability in a variety of areas such engineering, management, the military and other …