Multi-objective evolutionary algorithms (MOEAs) have shown promising performance in
solving various optimization problems, but their performance may deteriorate drastically …

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

The flexible job shop scheduling problem (FJSP) is significant for realistic manufacturing.
However, the job processing time usually is uncertain and changeable during …

In vehicular edge computing (VEC), vehicle users (VUs) can offload their computation-
intensive tasks to edge server (ES) that provides additional computation resources. Due to …

In the traditional cloud-based Internet of Vehicles (IoV) architecture, it is difficult to guarantee
the low latency requirements of the current intelligent transportation system (ITS). As a …

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 …

Green flexible job-shop scheduling problem (FJSP) aims to improve profit and reduce
energy consumption for modern manufacturing. Meanwhile, FJSP with type-2 fuzzy …

With increasing environmental awareness and energy requirement, sustainable
manufacturing has attracted growing attention. Meanwhile, there is a high level of …

The development of the Internet of Vehicles (IoV) has made transportation systems into
intelligent networks. However, with the increase in vehicles, an increasing number of data …

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 …