Now showing items 1-4 of 4
Scalarizing functions in decomposition-based multiobjective evolutionary algorithms
(IEEE Press, 2017)
Decomposition-based multiobjective evolutionary algorithms have received increasing research interests due to their high performance for solving multiobjective optimization problems. However, scalarizing functions, which ...
A knee-point-based evolutionary algorithm using weighted subpopulation for many-objective optimization
Among many-objective optimization problems (MaOPs), the proportion of nondominated solutions is too large to distinguish among different solutions, which is a great obstacle in the process of solving MaOPs. Thus, this paper ...
A decomposition-based multiobjective evolutionary algorithm with angle-based adaptive penalty
A multiobjective evolutionary algorithm based on decomposition (MOEA/D) decomposes a multiobjective optimization problem (MOP) into a number of scalar optimization subproblems and optimizes them in a collaborative manner. ...
A Pareto-based evolutionary algorithm using decomposition and truncation for dynamic multi-objective optimization
Maintaining a balance between convergence and diversity of the population in the objective space has been widely recognized as the main challenge when solving problems with two or more conflicting objectives. This is added ...