Post-Randomization Method

Keyword(s):  
2021 ◽  
Vol 50 (1) ◽  
pp. 5-12
Author(s):  
Hani Alquhayz ◽  
Mahdi Jemmali

This paper focuses on the maximization of the minimum completion time on identical parallel processors. The objective of this maximization is to ensure fair distribution. Let a set of jobs to be assigned to several identical parallel processors. This problem is shown as NP-hard. The research work of this paper is based essentially on the comparison of the proposed heuristics with others cited in the literature review. Our heuristics are developed using essentially the randomization method and the iterative utilization of the knapsack problem to solve the studied problem. Heuristics are assessed by several instances represented in the experimental results. The results show that the knapsack based heuristic gives almost a similar performance than heuristic in a literature review but in better running time.  


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Dmitriy Kolyukhin

Abstract The paper addresses a global sensitivity analysis of complex models. The work presents a generalization of the hierarchical statistical models where uncertain parameters determine the distribution of statistical models. The double randomization method is applied to increase the efficiency of the Monte Carlo estimation of Sobol indices. Numerical computations are provided to study the accuracy and efficiency of the proposed technique. The issue of optimization of the suggested approach is considered.


Ecosphere ◽  
2011 ◽  
Vol 2 (8) ◽  
pp. art94 ◽  
Author(s):  
K. A. Harper ◽  
S. E. Macdonald

2019 ◽  
Vol 13 (2) ◽  
pp. 40
Author(s):  
Rio Priantama ◽  
Yuda Priandani

The conventional learning process carried out face-to-face, is less effective as a source of learning, because the focus of students' interest has now shifted to their device so that students have difficulty repeating learning material. This study aims to produce learning media based on mobile learning on the android platform which is used as a source of learning fiqh applications for students. This mobile learning application is built by applying the Fisher Yates Shuffling algorithm or commonly known as the Fisher Yates algorithm which is now widely used in the process of developing randomization applications. This randomization method is the optimal randomization method in application development, being able to randomize the amount of material about the science of jurisprudence and prevent cheating users who only memorize answers without understanding the material when the questions are fixed or not random. Applications are built using MySQL as a database designed to manage and manipulate data quickly and easily. PHP and Perl are used as scripting programming languages for the internet and collaborate on the Android platform. The system development method used is RUP (Rational Unified Process) by collecting various best practices found in the software development industry.System testing is done using a white box and black box testing shows that the Fisher Yates algorithm can be applied in the mobile learning quiz application as a randomizer about questions. User Acceptance Model (UAT) test results show that this mobile learning application can help the process of learning the science of jurisprudence as well as being a reference in seeing the ability of students to learn the science of jurisprudence. Keywords: Mobile learning, Fisher Yates Algorithm, Fiqih, MySQL, RUP, UML


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