Abstract
Today, there is a need to manage composite patents based on emerging technologies in business. The research related to ranking candidate patents and selecting optimization strategies does not consider the constraints of non-functional properties. This paper proposes a method for incorporating the GA and rough set theory that can (i) solve problems that can be decomposed into functional requirements, and (ii) improve GA performance by reducing the range of the initial population and constrained crossover using rough set theory. Based on our experimental results, this approach has shown great promise and operates effectively.
| Original language | English |
|---|---|
| Pages (from-to) | 39-55 |
| Number of pages | 17 |
| Journal | International Journal of Information and Management Sciences |
| Volume | 24 |
| Issue number | 1 |
| Publication status | Published - 2013 Mar 1 |
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All Science Journal Classification (ASJC) codes
- Industrial and Manufacturing Engineering
- Control and Systems Engineering
- Management Information Systems
- Strategy and Management
- Information Systems and Management
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The genetic algorithm with rough set theory incorporated into the patent composition. / Liang, Wen Yau; Huang, Chun Che.
In: International Journal of Information and Management Sciences, Vol. 24, No. 1, 01.03.2013, p. 39-55.Research output: Contribution to journal › Article
TY - JOUR
T1 - The genetic algorithm with rough set theory incorporated into the patent composition
AU - Liang, Wen Yau
AU - Huang, Chun Che
PY - 2013/3/1
Y1 - 2013/3/1
N2 - Today, there is a need to manage composite patents based on emerging technologies in business. The research related to ranking candidate patents and selecting optimization strategies does not consider the constraints of non-functional properties. This paper proposes a method for incorporating the GA and rough set theory that can (i) solve problems that can be decomposed into functional requirements, and (ii) improve GA performance by reducing the range of the initial population and constrained crossover using rough set theory. Based on our experimental results, this approach has shown great promise and operates effectively.
AB - Today, there is a need to manage composite patents based on emerging technologies in business. The research related to ranking candidate patents and selecting optimization strategies does not consider the constraints of non-functional properties. This paper proposes a method for incorporating the GA and rough set theory that can (i) solve problems that can be decomposed into functional requirements, and (ii) improve GA performance by reducing the range of the initial population and constrained crossover using rough set theory. Based on our experimental results, this approach has shown great promise and operates effectively.
UR - http://www.scopus.com/inward/record.url?scp=84879857135&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84879857135&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84879857135
VL - 24
SP - 39
EP - 55
JO - International Journal of Information and Management Sciences
JF - International Journal of Information and Management Sciences
SN - 1017-1819
IS - 1
ER -