In the last two decades, the fast and elitist non-dominated sorting genetic algorithm (NSGA-
II) has attracted extensive research interests, and it is still one of the hottest research …

Realistic problems typically have many conflicting objectives. Therefore, it is instinctive to
look at the engineering problems as multi-objective optimization problems. This paper briefly …

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

Multiobjective reliability-based design optimization (RBDO) is a research area, which has
not been investigated in the literatures comparing with single-objective RBDO. This work …

Urban form significantly influences building energy consumption. However, most research
has primarily focused on quantifying the relationship between the two factors, with limited …

Research in metaheuristics for global optimization problems are currently experiencing an
overload of wide range of available metaheuristic-based solution approaches. Since the …

Abstract Generally, Synthetic Benchmark Problems (SBPs) are utilized to assess the
performance of metaheuristics. However, these SBPs may include various unrealistic …

In almost no other field of computer science, the idea of using bio-inspired search paradigms
has been so useful as in solving multiobjective optimization problems. The idea of using 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 …

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