Solving a new multi-objective hybrid flexible flowshop problem with limited waiting times and machine-sequence-dependent set-up time constraints

2013 ◽  
Vol 27 (5) ◽  
pp. 450-469 ◽  
Author(s):  
S.F. Attar ◽  
M. Mohammadi ◽  
R. Tavakkoli-Moghaddam ◽  
S. Yaghoubi
Keyword(s):  
Waiting Times ◽  
Time Constraints ◽  
Multi Objective ◽  
Machine Sequence ◽  
Flexible Flowshop ◽  
Sequence Dependent ◽  
Set Up ◽  
Hybrid Flexible Flowshop ◽  
Flowshop Problem

scholarly journals Metaheuristics for the multi-objective FJSP with sequence-dependent set-up times, auxiliary resources and machine down time

2009 ◽  
Vol 180 (1) ◽  
pp. 165-196 ◽  
Author(s):  
Jacomine Grobler ◽  
Andries P. Engelbrecht ◽  
Schalk Kok ◽  
Sarma Yadavalli
Keyword(s):  
Multi Objective ◽  
Sequence Dependent ◽  
Set Up

Applications of Multiple Objective Genetic Algorithms in the Optimization Design of Tracked Self-Moving Power’s Layout

2013 ◽  
Vol 307 ◽  
pp. 161-165
Author(s):  
Hai Jin ◽  
Jin Fa Xie
Keyword(s):  
Optimization Design ◽  
Pareto Front ◽  
Layout Optimization ◽  
Multiple Objective ◽  
Multi Objective Optimization ◽  
Layout Problem ◽  
Basic Principles ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Set Up

A multi-objective genetic algorithm is applied into the layout optimization of tracked self-moving power. The layout optimization mathematical model was set up. Then introduced the basic principles of NSGA-Ⅱ, which is a Pareto multi-objective optimization algorithm. Finally, NSGA-Ⅱwas presented to solve the layout problem. The algorithm was proved to be effective by some practical examples. The results showed that the algorithm can spread toward the whole Pareto front, and provide many reasonable solutions once for all.

Virtual Machines Scheduling Algorithm Based on Multi-Objective Optimization in Cloud Computing

2014 ◽  
Vol 1046 ◽  
pp. 508-511
Author(s):  
Jian Rong Zhu ◽  
Yi Zhuang ◽  
Jing Li ◽  
Wei Zhu
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Machine Scheduling ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Virtual Machine Scheduling ◽  
Set Up

How to reduce energy consumption while improving utility of datacenter is one of the key technologies in the cloud computing environment. In this paper, we use energy consumption and utility of data center as objective functions to set up a virtual machine scheduling model based on multi-objective optimization VMSA-MOP, and design a virtual machine scheduling algorithm based on NSGA-2 to solve the model. Experimental results show that compared with other virtual machine scheduling algorithms, our algorithm can obtain relatively optimal scheduling results.

Sign in / Sign up

Export Citation Format

Share Document