MIP-based GRASP and Genetic Algorithm for Balancing Transfer Lines

2009 ◽  
pp. 189-208 ◽  
Author(s):  
Alexandre Dolgui ◽  
Anton Eremeev ◽  
Olga Guschinskaya
Keyword(s):  
Genetic Algorithm ◽  
Transfer Lines

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

Use of vent stack temperature as a feedforward variable for dissolver total titratable alkali (TTA) control

TAPPI Journal ◽  
2018 ◽  
Vol 17 (05) ◽  
pp. 261-269
Author(s):  
Wei Ren ◽  
Brennan Dubord ◽  
Jason Johnson ◽  
Bruce Allison
Keyword(s):  
Feedback Control ◽  
Current Practice ◽  
Feedforward Control ◽  
Control Variable ◽  
Indirect Measurement ◽  
Tight Control ◽  
Transfer Lines ◽  
Green Liquor ◽  
Process Dynamics ◽  
Downstream Processes

Tight control of raw green liquor total titratable alkali (TTA) may be considered an important first step towards improving the overall economic performance of the causticizing process. Dissolving tank control is made difficult by the fact that the unknown smelt flow is highly variable and subject to runoff. High TTA variability negatively impacts operational costs through increased scaling in the dissolver and transfer lines, increased deadload in the liquor cycle, under- and over-liming, increased energy consumption, and increased maintenance. Current practice is to use feedback control to regulate the TTA to a target value through manipulation of weak wash flow while simultaneously keeping dissolver density within acceptable limits. Unfortunately, the amount of variability reduction that can be achieved by feedback control alone is fundamentally limited by the process dynamics. One way to improve upon the situation would be to measure the smelt flow and use it as a feedforward control variable. Direct measurement of smelt flow is not yet possible. The use of an indirect measurement, the dissolver vent stack temperature, is investigated in this paper as a surrogate feedforward variable for dissolving tank TTA control. Mill trials indicate that significant variability reduction in the raw green liquor TTA is possible and that the control improvements carry through to the downstream processes.

Recycling Lethal Chromosomes Based on Immune Operation in Genetic Algorithm for Multi-Knapsack Problem

2014 ◽  
Vol 1 ◽  
pp. 219-222
Author(s):  
Jing Guo ◽  
Jousuke Kuroiwa ◽  
Hisakazu Ogura ◽  
Izumi Suwa ◽  
Haruhiko Shirai ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Knapsack Problem
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