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...

NSGA methodology discussed in Section 3.1 suffers from three weaknesses: computational complexity, non-elitist approach and the need to specify a sharing parameter. An improved version of NSGA known as NSGA-II, which resolved the above problems and uses elitism to create a diverse Pareto-optimal front, has been subsequently presented (Deb et al 2002). The main features of NSGA-II are low comput...

The following paper describes a cooperative coevolutionary algorithm which incorporates a novel collaboration formation mechanism. It encourages rewarding of components participating in successful collaborations from each sub-population. The successfulness of the collaboration is measured by a non-dominated sorting procedure. The algorithm has demonstrated it can perform comparably with the NSG...

This paper introduces a modified PSO, Non-dominated Sorting Particle Swarm Optimizer (NSPSO), for better multiobjective optimization. NSPSO extends the basic form of PSO by making a better use of particles’ personal bests and offspring for more effective nondomination comparisons. Instead of a single comparison between a particle’s personal best and its offspring, NSPSO compares all particles’ ...

many studies are performed by researchers about shell and tube heat exchanger but the multi-objective big bang-big crunch algorithm (mobba) technique has never been used in such studies. this paper presents application of thermal-economic multi-objective optimization of shell and tube heat exchanger using mobba. for optimal design of a shell and tube heat exchanger, it was first thermally model...

integrated production-distribution planning (pdp) is one of the most important approaches in supply chain networks. we consider a supply chain network (scn) to consist of multi suppliers, plants, distribution centers (dcs), and retailers. a bi-objective mixed integer linear programming model for integrating production-distribution designed here aim to simultaneously minimize total net costs in ...