In the last 20 years, evolutionary algorithms (EAs) have shown to be an effective method to
solve multiobjective optimization problems (MOPs). Due to their population-based nature …

There exist many multiobjective optimization problems (MOPs) containing a large number of
decision variables in real-world applications, which are known as large-scale MOPs. Due to …

Due to the curse of dimensionality of search space, it is extremely difficult for evolutionary
algorithms to approximate the optimal solutions of large-scale multiobjective optimization …

In the area of reservoir engineering, the optimization of oil and gas production is a complex
task involving a myriad of interconnected decision variables sha** the production system's …

The first cooperative co-evolutionary algorithm (CCEA) was proposed by Potter and De Jong
in 1994 and since then many CCEAs have been proposed and successfully applied to …

In this paper, we propose a new method for solving multiobjective optimization problems
with a large number of decision variables. The proposed method called weighted …

Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

In addition to the need for satisfying several competing objectives, many real-world
applications are also dynamic and require the optimization algorithm to track the changing …

Air traffic flow management (ATFM) is the key driver of efficient aviation. It aims at balancing
traffic demand against airspace capacity by scheduling aircraft, which is critical for air …

Multi-objective particle swarm optimization (MOPSO) is an optimization technique inspired
by bird flocking, which has been steadily gaining attention from the research community …