Previous researchers have made impressive strides in develo** algorithms and solution
methodologies to address multi-objective optimization (MOO) problems in industrial …

Evolutionary dynamic multi-objective optimisation (EDMO) is a relatively young but rapidly
growing area of investigation. EDMO employs evolutionary approaches to handle multi …

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

Planning a practical three-dimensional (3-D) flight path for unmanned aerial vehicles (UAVs)
is a key challenge for the follow-up management and decision making in disaster …

Over the last three decades, a large number of evolutionary algorithms have been
developed for solving multi-objective optimization problems. However, there lacks an upto …

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 …

During the past two decades, a variety of multiobjective evolutionary algorithms (MOEAs)
have been proposed in the literature. As pointed out in some recent studies, however, the …

Inverted generational distance (IGD) has been widely considered as a reliable performance
indicator to concurrently quantify the convergence and diversity of multiobjective and many …

In evolutionary multiobjective optimization, maintaining a good balance between
convergence and diversity is particularly crucial to the performance of the evolutionary …

In order to alleviate the resource depletion as well as achieve decarbonization, develo**
renewable energy system is a feasible solution. This paper establishes a wind-photovoltaic …