A computation method for evaluating importance-measures of gates in a fault tree

Lee, Hae Sang; Lie, Chang-Hoon; Hong, Jung Sik

doi:10.1109/24.664007

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2000

2015

Publication Types

Select...

Article3

Other3

Relationship

Self Cite0

Independent6

Authors

Journals

Cited by 10 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Knapsack problem [1][2][3][4][5][6][7] is a well-known and well-studied problem in combinatorial optimization. It has a wide range of applications, for example network planning, network routing, parallel scheduling, and budgeting etc..…”

Section: Introductionmentioning

confidence: 99%

A Genetic Algorithm for Solving Knapsack Problems Based on Adaptive Evolution in Dual Population

Yan

Guo

et al. 2013

AMR

View full text Add to dashboard Cite

In order to solve knapsack problems efficiently, an improved genetic algorithm based on adaptive evolution in dual population (called DPAGA) is proposed. In DPAGA, the new population produced by selecting operation is regarded as main population. The population composed by the individuals washed out by selecting operation is regarded as subordinate population. The individual evolution strategy of main population is different from that of subordinate population. The crossover operators and mutation operators are all adjusted non-linearly and adaptively. DPAGA is used to solve knapsack problems. The experimental results show that its convergence speed and solution quality are all better then that of simple genetic algorithm. It is also suited to solve other optimization problems.

show abstract

Section: Introductionmentioning

confidence: 99%