A novel scheduling model for computational grid using quantum genetic algorithm

2013 ◽  
Vol 65 (2) ◽  
pp. 742-770 ◽  
Author(s):  
Shiv Prakash ◽  
Deo Prakash Vidyarthi
Author(s):  
Zahid Raza ◽  
Deo P. Vidyarthi

Scheduling on distributed systems is an NP hard problem and grid being a wide heterogeneous expandable system makes scheduling even a tougher job. Genetic algorithm, based on natural selection and evolution has gained popularity in recent times because of its effectiveness in handling optimization problems. In this article, a job-scheduling model for a computational grid with the objective of minimizing the turnaround time using genetic algorithm is proposed. The model evaluates various clusters in the grid to find the most suitable one with minimum turnaround time for the job-scheduling. Simulation studies compare the performance of this model with other similar models.


2012 ◽  
Vol 253-255 ◽  
pp. 1406-1409 ◽  
Author(s):  
Xin Lai Tang ◽  
Shu Hong Yang

Considering the influence that the cycles of signal lamp have on the waiting time, a bus scheduling model is presented in this paper based on the trade-off between the cost of bus operator and benefits of passengers. In order to handle with the low efficiency brought about by the refused strategy, a new fitness function is designed according to penalty strategy, and then traditional genetic algorithm is replaced by quantum genetic algorithm to accelerate the search of optimal parameters further. The results of experiment show that the presented method is effective.


Proceedings ◽  
2019 ◽  
Vol 46 (1) ◽  
pp. 26
Author(s):  
Pranjal Sharma ◽  
Ankit Agarwal ◽  
Bhawna Chaudhary

In recent years, geologists have put in a lot of effort trying to study the evolution of Earth using different techniques studying rocks, gases, and water at different channels like mantle, lithosphere, and atmosphere. Some of the methods include estimation of heat flux between the atmosphere and sea ice, modeling global temperature changes, and groundwater monitoring networks. That being said, algorithms involving the study of Earth’s evolution have been a debated topic for decades. In addition, there is distinct research on the mantle, lithosphere, and atmosphere using isotopic fractionation, which this paper will take into consideration to form genes at the former stage. This factor of isotopic fractionation could be molded in QGA to study the Earth’s evolution. We combined these factors because the gases containing these isotopes move from mantle to lithosphere or atmosphere through gaps or volcanic eruptions contributing to it. We are likely to use the Rb/Sr and Sm/Nd ratios to study the evolution of these channels. This paper, in general, provides the idea of gathering some information about temperature changes by using isotopic ratios as chromosomes, in QGA the chromosomes depict the characteristic of a generation. Here these ratios depict the temperature characteristic and other steps of QGA would be molded to study these ratios in the form of temperature changes, which would further signify the evolution of Earth based on the study that temperature changes with the change in isotopic ratios. This paper will collect these distinct studies and embed them into an upgraded quantum genetic algorithm called Quantum Genetic Terrain Algorithm or Quantum GTA.


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