Solving JSSP by Introducing Hamilton Similarity and Time Dependent Fitness Scaling

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Izvoz citacije: ABNT
ABRASHI, Arijan ;ŠTEFANIĆ, Nedjeljko ;LISJAK, Dragutin .
Solving JSSP by Introducing Hamilton Similarity and Time Dependent Fitness Scaling. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 56, n.5, p. 330-339, october 2017. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/sl/article/solving-jssp-by-introducing-hamilton-similarity-and-time-dependent-fitness-scaling/>. Date accessed: 18 jan. 2020. 
doi:http://dx.doi.org/.
Abrashi, A., Štefanić, N., & Lisjak, D.
(2010).
Solving JSSP by Introducing Hamilton Similarity and Time Dependent Fitness Scaling.
Strojniški vestnik - Journal of Mechanical Engineering, 56(5), 330-339.
doi:http://dx.doi.org/
@article{.,
	author = {Arijan  Abrashi and Nedjeljko  Štefanić and Dragutin  Lisjak},
	title = {Solving JSSP by Introducing Hamilton Similarity and Time Dependent Fitness Scaling},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {56},
	number = {5},
	year = {2010},
	keywords = {genetic algorithm; Hamilton similarity; niching; time dependent fitness scaling; Job shop scheduling problem; },
	abstract = {In this paper we propose and test a niching genetic algorithm (GA), which uses the so-called Hamilton similarity for a comparison of individuals in the population. The advantage of the Hamilton similarity lies in the fact that there is no need for context sensitive information in order to successfully compare two population members. Furthermore, the algorithm was tested on the famous Job Shop Scheduling Problem (JSSP) - benchmark mt10, and statistical results of the test were given. Significantly smaller standard deviation of the proposed GA compared to Simple GA clearly demonstrates its superiority. In addition to the Hamilton similarity, time dependent fitness scaling was proposed which in conjunction with niching significantly reduces the probability of the algorithm to get stuck in one of the less desirable local optimum. Finally, suggestions for future research are given.},
	issn = {0039-2480},	pages = {330-339},	doi = {},
	url = {https://www.sv-jme.eu/sl/article/solving-jssp-by-introducing-hamilton-similarity-and-time-dependent-fitness-scaling/}
}
Abrashi, A.,Štefanić, N.,Lisjak, D.
2010 October 56. Solving JSSP by Introducing Hamilton Similarity and Time Dependent Fitness Scaling. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 56:5
%A Abrashi, Arijan 
%A Štefanić, Nedjeljko 
%A Lisjak, Dragutin 
%D 2010
%T Solving JSSP by Introducing Hamilton Similarity and Time Dependent Fitness Scaling
%B 2010
%9 genetic algorithm; Hamilton similarity; niching; time dependent fitness scaling; Job shop scheduling problem; 
%! Solving JSSP by Introducing Hamilton Similarity and Time Dependent Fitness Scaling
%K genetic algorithm; Hamilton similarity; niching; time dependent fitness scaling; Job shop scheduling problem; 
%X In this paper we propose and test a niching genetic algorithm (GA), which uses the so-called Hamilton similarity for a comparison of individuals in the population. The advantage of the Hamilton similarity lies in the fact that there is no need for context sensitive information in order to successfully compare two population members. Furthermore, the algorithm was tested on the famous Job Shop Scheduling Problem (JSSP) - benchmark mt10, and statistical results of the test were given. Significantly smaller standard deviation of the proposed GA compared to Simple GA clearly demonstrates its superiority. In addition to the Hamilton similarity, time dependent fitness scaling was proposed which in conjunction with niching significantly reduces the probability of the algorithm to get stuck in one of the less desirable local optimum. Finally, suggestions for future research are given.
%U https://www.sv-jme.eu/sl/article/solving-jssp-by-introducing-hamilton-similarity-and-time-dependent-fitness-scaling/
%0 Journal Article
%R 
%& 330
%P 10
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 56
%N 5
%@ 0039-2480
%8 2017-10-24
%7 2017-10-24
Abrashi, Arijan, Nedjeljko  Štefanić, & Dragutin  Lisjak.
"Solving JSSP by Introducing Hamilton Similarity and Time Dependent Fitness Scaling." Strojniški vestnik - Journal of Mechanical Engineering [Online], 56.5 (2010): 330-339. Web.  18 Jan. 2020
TY  - JOUR
AU  - Abrashi, Arijan 
AU  - Štefanić, Nedjeljko 
AU  - Lisjak, Dragutin 
PY  - 2010
TI  - Solving JSSP by Introducing Hamilton Similarity and Time Dependent Fitness Scaling
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - genetic algorithm; Hamilton similarity; niching; time dependent fitness scaling; Job shop scheduling problem; 
N2  - In this paper we propose and test a niching genetic algorithm (GA), which uses the so-called Hamilton similarity for a comparison of individuals in the population. The advantage of the Hamilton similarity lies in the fact that there is no need for context sensitive information in order to successfully compare two population members. Furthermore, the algorithm was tested on the famous Job Shop Scheduling Problem (JSSP) - benchmark mt10, and statistical results of the test were given. Significantly smaller standard deviation of the proposed GA compared to Simple GA clearly demonstrates its superiority. In addition to the Hamilton similarity, time dependent fitness scaling was proposed which in conjunction with niching significantly reduces the probability of the algorithm to get stuck in one of the less desirable local optimum. Finally, suggestions for future research are given.
UR  - https://www.sv-jme.eu/sl/article/solving-jssp-by-introducing-hamilton-similarity-and-time-dependent-fitness-scaling/
@article{{}{.},
	author = {Abrashi, A., Štefanić, N., Lisjak, D.},
	title = {Solving JSSP by Introducing Hamilton Similarity and Time Dependent Fitness Scaling},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {56},
	number = {5},
	year = {2010},
	doi = {},
	url = {https://www.sv-jme.eu/sl/article/solving-jssp-by-introducing-hamilton-similarity-and-time-dependent-fitness-scaling/}
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TY  - JOUR
AU  - Abrashi, Arijan 
AU  - Štefanić, Nedjeljko 
AU  - Lisjak, Dragutin 
PY  - 2017/10/24
TI  - Solving JSSP by Introducing Hamilton Similarity and Time Dependent Fitness Scaling
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 56, No 5 (2010): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - genetic algorithm, Hamilton similarity, niching, time dependent fitness scaling, Job shop scheduling problem, 
N2  - In this paper we propose and test a niching genetic algorithm (GA), which uses the so-called Hamilton similarity for a comparison of individuals in the population. The advantage of the Hamilton similarity lies in the fact that there is no need for context sensitive information in order to successfully compare two population members. Furthermore, the algorithm was tested on the famous Job Shop Scheduling Problem (JSSP) - benchmark mt10, and statistical results of the test were given. Significantly smaller standard deviation of the proposed GA compared to Simple GA clearly demonstrates its superiority. In addition to the Hamilton similarity, time dependent fitness scaling was proposed which in conjunction with niching significantly reduces the probability of the algorithm to get stuck in one of the less desirable local optimum. Finally, suggestions for future research are given.
UR  - https://www.sv-jme.eu/sl/article/solving-jssp-by-introducing-hamilton-similarity-and-time-dependent-fitness-scaling/
Abrashi, Arijan, Štefanić, Nedjeljko, AND Lisjak, Dragutin.
"Solving JSSP by Introducing Hamilton Similarity and Time Dependent Fitness Scaling" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 56 Number 5 (24 October 2017)

Avtorji

Inštitucije

  • Energy and Environmental Protection Institute, Croatia
  • Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Croatia
  • Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Croatia

Informacije o papirju

Strojniški vestnik - Journal of Mechanical Engineering 56(2010)5, 330-339

In this paper we propose and test a niching genetic algorithm (GA), which uses the so-called Hamilton similarity for a comparison of individuals in the population. The advantage of the Hamilton similarity lies in the fact that there is no need for context sensitive information in order to successfully compare two population members. Furthermore, the algorithm was tested on the famous Job Shop Scheduling Problem (JSSP) - benchmark mt10, and statistical results of the test were given. Significantly smaller standard deviation of the proposed GA compared to Simple GA clearly demonstrates its superiority. In addition to the Hamilton similarity, time dependent fitness scaling was proposed which in conjunction with niching significantly reduces the probability of the algorithm to get stuck in one of the less desirable local optimum. Finally, suggestions for future research are given.

genetic algorithm; Hamilton similarity; niching; time dependent fitness scaling; Job shop scheduling problem;