.png){kind=icon}
.png){kind=icon}
Return
A genetic algorithm method for one-dimensional machine location problems
.png){kind=icon}
PRE
AI
DOI：10.1016/S0925-5273(98)00163-7.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
One goal of designing a generalized flow line is to minimize the backtracking of jobs, i.e., to assign M machines to M locations along a linear track to minimize the total backtracking movements of jobs. It can be formulated as a quadratic assignment problem which is a difficult task to solve. In this paper, a genetic algorithm method is proposed and compared with some other methods. It is shown that the genetic algorithm method can find good quality solution effectively. (C) 1999 Published by Elsevier Science B.V. All rights reserved.
Keywords:
generalized flow line
backtracking
genetic algorithms
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
10
Papers:
7.9K
Citations:
3.6W
Organization
No organization information available