Complexity and variety of modern multiobjective optimisation problems result in the
emergence of numerous search techniques, from traditional mathematical programming to …

With modern requirements, there is an increasing tendency of considering multiple
objectives/criteria simultaneously in many Software Engineering (SE) scenarios. Such a …

Although synthetic test problems are widely used for the performance assessment of
evolutionary multi-objective optimization algorithms, they are likely to include unrealistic …

Both convergence and diversity are crucial to evolutionary many-objective optimization,
whereas most existing dominance relations show poor performance in balancing them, thus …

In real-world applications, there exist a lot of multiobjective optimization problems whose
Pareto-optimal solutions are sparse, that is, most variables of these solutions are 0 …

Nowadays, operation managers usually need efficient supply chain networks including
important design factors such as economic and social considerations. The recent decade …

The design of efficient energy systems, through the development of new technologies and
the improvement of current ones, requires the use of rigorous process synthesis methods for …

In many-objective optimization problems (MaOPs), forming sound tradeoffs between
convergence and diversity for the environmental selection of evolutionary algorithms is a …

Large-scale sparse multi-objective optimization problems exist widely in the real world, but
most existing evolutionary algorithms encounter great difficulties in solving the problems of …

PlatEMO is an open-source platform for solving complex optimization problems, which
provides a variety of metaheuristics including evolutionary algorithms, swarm intelligence …