Numerical Realization of the Simplex Algorithm

1983 ◽  
pp. 115-133
Author(s):  
Klaus Glashoff ◽  
Sven-Åke Gustafson
Keyword(s):  
Simplex Algorithm ◽  
Numerical Realization

Efficiency of the Network Simplex Algorithm for the Maximum Flow Problem

1988 ◽  
Author(s):  
Andrew V. Goldberg ◽  
Michael D. Grigoriadis ◽  
Robert E. Tarjan
Keyword(s):  
Flow Problem ◽  
Maximum Flow ◽  
Simplex Algorithm ◽  
Maximum Flow Problem ◽  
Network Simplex Algorithm ◽  
Network Simplex

scholarly journals Multi-user Remote Lab: Timetable Scheduling Using Simplex Nondominated Sorting Genetic Algorithm

2021 ◽  
Vol 2 (2) ◽  
pp. 1-13
Author(s):  
Seid Miad Zandavi ◽  
Vera Chung ◽  
Ali Anaissi
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Heuristic Algorithms ◽  
Simplex Algorithm ◽  
Local Optimum ◽  
Hybrid Optimization Algorithm ◽  
Multimodal Function ◽  
Remote Laboratories ◽  
Remote Lab ◽  
Timetable Problem

The scheduling of multi-user remote laboratories is modeled as a multimodal function for the proposed optimization algorithm. The hybrid optimization algorithm, hybridization of the Nelder-Mead Simplex algorithm, and Non-dominated Sorting Genetic Algorithm (NSGA), named Simplex Non-dominated Sorting Genetic Algorithm (SNSGA), is proposed to optimize the timetable problem for the remote laboratories to coordinate shared access. The proposed algorithm utilizes the Simplex algorithm in terms of exploration and NSGA for sorting local optimum points with consideration of potential areas. SNSGA is applied to difficult nonlinear continuous multimodal functions, and its performance is compared with hybrid Simplex Particle Swarm Optimization, Simplex Genetic Algorithm, and other heuristic algorithms. The results show that SNSGA has a competitive performance to address timetable problems.

Simplex-Based Calibration of Traffic Microsimulation Models with Intelligent Transportation Systems Data

2003 ◽  
Vol 1855 (1) ◽  
pp. 80-89 ◽  
Author(s):  
Kyu-Ok Kim ◽  
L. R. Rilett
Keyword(s):  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
System Modeling ◽  
Intelligent Transportation ◽  
Simplex Algorithm ◽  
Transportation System ◽  
Transportation Systems ◽  
Test Bed ◽  
Morning Peak ◽  
Microsimulation Models

In recent years, microsimulation has become increasingly important in transportation system modeling. A potential issue is whether these models adequately represent reality and whether enough data exist with which to calibrate these models. There has been rapid deployment of intelligent transportation system (ITS) technologies in most urban areas of North America in the last 10 years. While ITSs are developed primarily for real-time traffic operations, the data are typically archived and available for traffic microsimulation calibration. A methodology, based on the sequential simplex algorithm, that uses ITS data to calibrate microsimulation models is presented. The test bed is a 23-km section of Interstate 10 in Houston, Texas. Two microsimulation models, CORSIM and TRANSIMS, were calibrated for two different demand matrices and three periods (morning peak, evening peak, and off-peak). It was found for the morning peak that the simplex algorithm had better results then either the default values or a simple, manual calibration. As the level of congestion decreased, the effectiveness of the simplex approach also decreased, as compared with standard techniques.

Controller Parameters Optimization of PWM Converter Based DFIG

2014 ◽  
Vol 672-674 ◽  
pp. 1012-1015
Author(s):  
He Zhu ◽  
Da Tian Xu ◽  
Hao Ran Zhao
Keyword(s):  
Control Strategy ◽  
Simplex Algorithm ◽  
Parameters Optimization ◽  
Pwm Converter ◽  
Stator Flux ◽  
Grid Side ◽  
Rotor Side Converter ◽  
Grid Side Converter ◽  
And Control ◽  
The Mathematical Model

Based on the mathematical model of the PWM converter, control strategy of the grid-side converter directed by the grid voltage and control strategy of the rotor-side converter directed by the stator flux were established combining the vector control theory. The method using the nonlinear simplex algorithm to optimize the PI control parameters of the DFIG unit was first proposed, optimization results proved that this method had good practicality and robustness.

Improving the modulo simplex algorithm for large-scale periodic timetabling

2013 ◽  
Vol 40 (5) ◽  
pp. 1363-1370 ◽  
Author(s):  
Marc Goerigk ◽  
Anita Schöbel
Keyword(s):  
Large Scale ◽  
Simplex Algorithm ◽  
Periodic Timetabling
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