Much attention has been paid to evolutionary multi-objective optimization approaches efficiently solve real-world engineering problems with multiple conflicting objectives. However, the loss of selection pressure and non-uniformity in distribution Pareto optimal solutions objective space can impede both dominance-based decomposition-based optimizers when solving many-objective problems. In this...

Cloud computing task scheduling is a multi-objective decision on how to perform a variety of tasks simultaneously reasonable sort is essential. Therefore, this article constructs a population of convergence non-dominated sorting method. This method is based on non-dominated sorting method; the use of distributed estimation method is improved by four steps to complete the task order scheduling. ...

the vehicle driving comfort has become one of the important factors of vehicle quality and receives increasing attention. in this paper, optimal points of vehicle suspension parameters are generated using modified non-dominated sorting genetic algorithm (nsga-ii) for pareto optimization of 5-degree of freedom vehicle vibration model considering three conflicting functions simultaneously. in thi...

Abstract. Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) computational complexity (where is the number of objectives and is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algor...

Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) O(mN3) computational complexity (where m is the number of objectives and N is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algo...