Now showing items 1-5 of 5
A grid-based evolutionary algorithm for many-objective optimization
Balancing convergence and diversity plays a key role in evolutionary multiobjective optimization (EMO). Most current EMO algorithms perform well on problems with two or three objectives, but encounter difficulties in their ...
Shift-based density estimation for Pareto-based algorithms in many-objective optimization
(IEEE Press, 2013-05-16)
It is commonly accepted that Pareto-based evolutionary multiobjective optimization (EMO) algorithms encounter difficulties in dealing with many-objective problems. In these algorithms, the ineffectiveness of the Pareto ...
Evolutionary algorithms with segment-based search for multiobjective optimization problems
(IEEE Press, 2013-10-10)
This paper proposes a variation operator, called segment-based search (SBS), to improve the performance of evolutionary algorithms on continuous multiobjective optimization problems. SBS divides the search space into many ...
IPESA-II: Improved Pareto envelope-based selection algorithm II