scholarly journals Pivoting rules for the revised simplex algorithm

2014 ◽  
Vol 24 (3) ◽  
pp. 321-332 ◽  
Author(s):  
Nikolaos Ploskas ◽  
Nikolaos Samaras
Keyword(s):  
Execution Time ◽  
Computational Study ◽  
Simplex Algorithm ◽  
Total Execution Time ◽  
Nonbasic Variable ◽  
Significant Step ◽  
Test Sets ◽  
Revised Simplex Algorithm ◽  
Pricing Rule

Pricing is a significant step in the simplex algorithm where an improving nonbasic variable is selected in order to enter the basis. This step is crucial and can dictate the total execution time. In this paper, we perform a computational study in which the pricing operation is computed with eight different pivoting rules: (i) Bland?s Rule, (ii) Dantzig?s Rule, (iii) Greatest Increment Method, (iv) Least Recently Considered Method, (v) Partial Pricing Rule, (vi) Queue Rule, (vii) Stack Rule, and (viii) Steepest Edge Rule; and incorporate them with the revised simplex algorithm. All pivoting rules have been implemented in MATLAB. The test sets used in the computational study are a set of randomly generated optimal sparse and dense LPs and a set of benchmark LPs (Netliboptimal, Kennington, Netlib-infeasible).

Preemptive Scheduling for Two-Processor Systems

1988 ◽  
Vol 11 (1) ◽  
pp. 1-19
Author(s):  
Andrzej Rowicki
Keyword(s):  
Execution Time ◽  
Preemptive Scheduling ◽  
Total Execution Time ◽  
Schedule Length ◽  
Execution Times ◽  
Dependent Tasks

The purpose of the paper is to consider an algorithm for preemptive scheduling for two-processor systems with identical processors. Computations submitted to the systems are composed of dependent tasks with arbitrary execution times and contain no loops and have only one output. We assume that preemptions times are completely unconstrained, and preemptions consume no time. Moreover, the algorithm determines the total execution time of the computation. It has been proved that this algorithm is optimal, that is, the total execution time of the computation (schedule length) is minimized.

Effective Utilization of Resources Through Optimal Allocation and Opportunistic Migration of Virtual Machines in Cloud Environment

2021 ◽  
Vol 11 (3) ◽  
pp. 72-91
Author(s):  
Priyanka H. ◽  
Mary Cherian
Keyword(s):  
Data Center ◽  
Execution Time ◽  
Data Centers ◽  
Optimal Allocation ◽  
Virtual Machines ◽  
Large Data ◽  
Migration Time ◽  
Resource Usage ◽  
Total Execution Time ◽  
Effective Utilization

Cloud computing has become more prominent, and it is used in large data centers. Distribution of well-organized resources (bandwidth, CPU, and memory) is the major problem in the data centers. The genetically enhanced shuffling frog leaping algorithm (GESFLA) framework is proposed to select the optimal virtual machines to schedule the tasks and allocate them in physical machines (PMs). The proposed GESFLA-based resource allocation technique is useful in minimizing the wastage of resource usage and also minimizes the power consumption of the data center. The proposed GESFL algorithm is compared with task-based particle swarm optimization (TBPSO) for efficiency. The experimental results show the excellence of GESFLA over TBPSO in terms of resource usage ratio, migration time, and total execution time. The proposed GESFLA framework reduces the energy consumption of data center up to 79%, migration time by 67%, and CPU utilization is improved by 9% for Planet Lab workload traces. For the random workload, the execution time is minimized by 71%, transfer time is reduced up to 99%, and the CPU consumption is improved by 17% when compared to TBPSO.

Revised simplex algorithm for linear programming on GPUs with CUDA

2018 ◽  
Vol 77 (22) ◽  
pp. 30035-30050 ◽  
Author(s):  
Lili He ◽  
Hongtao Bai ◽  
Yu Jiang ◽  
Dantong Ouyang ◽  
Shanshan Jiang
Keyword(s):  
Linear Programming ◽  
Simplex Algorithm ◽  
Revised Simplex Algorithm

A Decision Support System for Solving Linear Programming Problems

2014 ◽  
Vol 6 (2) ◽  
pp. 46-62
Author(s):  
Nikolaos Ploskas ◽  
Nikolaos Samaras ◽  
Jason Papathanasiou
Keyword(s):  
Linear Programming ◽  
Decision Support ◽  
Simplex Algorithm ◽  
Decision Makers ◽  
Web Interface ◽  
Web Based ◽  
Linear Programming Problems ◽  
Revised Simplex Algorithm ◽  
The Given ◽  
Programming Algorithms

Linear programming algorithms have been widely used in Decision Support Systems. These systems have incorporated linear programming algorithms for the solution of the given problems. Yet, the special structure of each linear problem may take advantage of different linear programming algorithms or different techniques used in these algorithms. This paper proposes a web-based DSS that assists decision makers in the solution of linear programming problems with a variety of linear programming algorithms and techniques. Two linear programming algorithms have been included in the DSS: (i) revised simplex algorithm and (ii) exterior primal simplex algorithm. Furthermore, ten scaling techniques, five basis update methods and eight pivoting rules have been incorporated in the DSS. All linear programming algorithms and methods have been implemented using MATLAB and converted to Java classes using MATLAB Builder JA, while the web interface of the DSS has been designed using Java Server Pages.

Performance Analysis of the PISO-Based CFD Simulation

2014 ◽  
Vol 607 ◽  
pp. 872-876 ◽  
Author(s):  
Xiao Guang Ren
Keyword(s):  
Performance Optimization ◽  
Execution Time ◽  
Cfd Simulation ◽  
Fluid Flows ◽  
Total Execution Time ◽  
Simulation Performance ◽  
Simulation Efficiency ◽  
Matrix Operations ◽  
The Matrix ◽  
Computational Fluid Dynamics Cfd

Computational Fluid Dynamics (CFD) is widely applied for the simulation of fluid flows, and the performance of the simulation process is critical for the simulation efficiency. In this paper, we analyze the performance of CFD simulation application with profiling technology, which gets the portions of the main parts’ execution time. Through the experiment, we find that the PISO algorithm has a significant impact on the CFD simulation performance, which account for more than 90% of the total execution time. The matrix operations are also account for more than 60% of the total execution time, which provides opportunity for performance optimization.

Research on MapReduce Task Dynamic Balancing Strategy Based on File Label

2014 ◽  
Vol 571-572 ◽  
pp. 17-21
Author(s):  
Rong Huang ◽  
An Ping Xiong ◽  
Yang Zou
Keyword(s):  
Execution Time ◽  
Task Assignment ◽  
Total Execution Time ◽  
Dynamic Balancing ◽  
Processing Efficiency ◽  
The Core ◽  
Different Types ◽  
Assignment Strategy ◽  
Computing Performance ◽  
Core Framework

MapReduce is one of the core framework of Hadoop, it’s computing performance has been widely concerned and researched. In heterogeneous environment, unreasonable map task assignments and inefficient resource utilization lead to multiple backup tasks and the job total execution time is poor.For these problems, this paper proposes a new map task assignment strategy, which is map task dynamic balancing strategy based on file label. The strategy marks on job according to the different types, estimates node computing capabilities and historical processing efficiency of each label task, ensures map task which was assigned can execute successfully. Experiments show that, the strategy can effectively reduce number of backup tasks in map phase, and to some extent optimize the total execution time of the job.

scholarly journals Indicators of Technical and Tactical Actions of Qualified Air Rifle Shooters

2019 ◽  
Vol 19 (4) ◽  
pp. 186-192
Author(s):  
A. P. Demichkovskyi
Keyword(s):  
Experimental Data ◽  
Detailed Analysis ◽  
Research Methods ◽  
Execution Time ◽  
Total Execution Time ◽  
Motor Abilities ◽  
Competitive Activity ◽  
Time Parameters ◽  
The Difference ◽  
Air Rifle

The purpose of the study was to define informative indicators of technical and tactical actions of qualified rifle shooting athletes. Materials and methods. The study involved MSU (number of athletes n = 10), CMSU (number of athletes n = 9). To solve the tasks set, the following research methods were used: analysis and generalization of scientific and methodological literature, pedagogical observation. Pedagogical observation was used to study the peculiarities of technical and tactical indicators of qualified athletes, as well as their motor abilities; methods of mathematical statistics were used to process the experimental data. Results. A detailed analysis of competitive activity made it possible to determine that the shot phases “Aiming”, “Shot execution – active shot”, “Preparation for the shot” are informative indicators of technical and tactical actions of qualified rifle shooting athletes. The study determined time parameters of the phases during competitive activity. The difference between the average indicators of the athletes with different sports qualifications is at the limit of 2.55 seconds, which suggests that the duration of the restorative processes of the shooter’s body affects the performance of each shot.  Conclusions. A detailed analysis of air rifle shooting among men during competitive activity allowed to determine the difference in technical and tactical fitness between the athletes with different sports qualifications of MSU and CMSU levels: “Aiming” – MSU 950.56 seconds, CMSU 1017.91 seconds; “Shot execution – active shot” – MSU 964.45 seconds, CMSU 952.36 seconds; “Preparation for the shot” – MSU 1678.66 seconds, CMSU 1855.19 seconds, “Total execution time” – MSU 3593.68 seconds, CMSU 3825.47 seconds.

Sign in / Sign up

Export Citation Format

Share Document