Genetic algorithm for balancing reconfigurable machining lines

2013 ◽  
Vol 66 (3) ◽  
pp. 541-547 ◽  
Author(s):  
Pavel A. Borisovsky ◽  
Xavier Delorme ◽  
Alexandre Dolgui
Keyword(s):  
Genetic Algorithm ◽  
Reconfigurable Machining ◽  
Machining Lines

Balancing reconfigurable machining lines by means of set partitioning model

2012 ◽  
Vol 45 (6) ◽  
pp. 426-431 ◽  
Author(s):  
Pavel A. Borisovsky ◽  
Xavier Delorme ◽  
Alexandre Dolgui
Keyword(s):  
Set Partitioning ◽  
Reconfigurable Machining ◽  
Machining Lines

scholarly journals Multi-Objective Approach for Production Line Equipment Selection

2012 ◽  
Vol 3 (1) ◽  
pp. 4-17 ◽  
Author(s):  
H. Chehade ◽  
A. Dolgui ◽  
F. Dugardin ◽  
L. Makdessian ◽  
F. Yalaoui
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Local Search ◽  
Production Line ◽  
Nsga Ii ◽  
Equipment Selection ◽  
Multi Objective ◽  
Numerical Tests ◽  
Machining Lines ◽  
Direct Measures

Multi-Objective Approach for Production Line Equipment Selection A novel problem dealing with design of reconfigurable automated machining lines is considered. Such lines are composed of workstations disposed sequentially. Each workstation needs the most suitable equipment. Each available piece of equipment is characterized by its cost, can perform a set of operations and requires skills of a given level for its maintenance. A multi-objective approach is proposed to assign tasks, choose and allocate pieces of equipment to workstations taking into account all the problem parameters and constraints. The techniques developed are based on a genetic algorithm of type NSGA-II. The NSGA-II suggested is also combined with a local search. These two genetic algorithms (with and without local search) are tested for several line examples and for two versions of the considered problem: bi-objective and four-objective cases. The results of numerical tests are reported. What is the most interesting is that the assessment of these algorithms is accomplished by using three measuring criteria: the direct measures of gaps, the measures proposed by Zitzler and Thiele in 1999 and the distances suggested by Riise in 2002.

Balancing reconfigurable machining lines via a set partitioning model

2013 ◽  
Vol 52 (13) ◽  
pp. 4026-4036 ◽  
Author(s):  
Pavel A. Borisovsky ◽  
Xavier Delorme ◽  
Alexandre Dolgui
Keyword(s):  
Set Partitioning ◽  
Reconfigurable Machining ◽  
Machining 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.

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