Evolutionary algorithms (EAs) are widely used to deal with optimization problems in dynamic environments (DE) [3]. When using EAs to solve DE problems, we are usually interested i...
Abstract- The Pareto optimal solutions to a multiobjective optimization problem often distribute very regularly in both the decision space and the objective space. Most existing ev...
Aimin Zhou, Qingfu Zhang, Yaochu Jin, Edward P. K....
Many-objective problems are difficult to solve using conventional multi-objective evolutionary algorithms (MOEAs) as these algorithms rely primarily on Pareto ranking to guide the ...
The resolution of a Multi-Objective Optimization Problem (MOOP) does not end when the Pareto-optimal set is found. In real problems, a single solution must be selected. Ideally, t...
In this paper we propose to use a distance metric based on user-preferences to efficiently find solutions for manyobjective problems. We use a particle swarm optimization (PSO) a...