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A genetic algorithm for interval nonlinear integer programming problem

delete1996-12-01
delete31
PRE
AI
T
Takao Yokota *
M
Mitsuo Gen
Y
Yinxiu Li
C
Chang-Eun Kim
DOI：10.1016/S0360-8352(96)00263-Xdelete
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Abstract

Abstract

En 中文
In this paper, we formulate an optimal design of system reliability problem as a nonlinear integer programming problem with interval coefficients, transform it into a single objective nonlinear integer programming problem without interval coefficients, and solve it directly with keeping nonlinearity of the objective function by using Genetic Algorithms (GA). Also, we demonstrate the efficiency of this method with incomplete Fault Detecting and Switching (FDS) for allocating redundant units.
Keywords:
nonlinear integer programming
interval coefficient
genetic algorithms
incomplete FDS
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Computers and Industrial Engineering cover
Computers and Industrial Engineering
IF:
6.5
Papers:
1.0W
Citations:
3.8W

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