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Search: subject:"Multi-population genetic algorithm"
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Algorithm
2
Algorithmus
2
Evolutionary algorithm
2
Evolutionärer Algorithmus
2
Distributed hybrid flow shop with unrelated parallel machines
1
Durchlaufzeit
1
Forecasting model
1
Greedy job insertion inter-factory neighbourhoods
1
Heuristics
1
Heuristik
1
Hong Kong offshore
1
Improved multi-population genetic algorithm
1
Lead time
1
Log-periodic power law model
1
Monthly power generation
1
Multi-Population Genetic Algorithm (MPGA)
1
Multi-criteria analysis
1
Multi-objective scheduling considering total tardiness
1
Multi-population genetic algorithm
1
Multikriterielle Entscheidungsanalyse
1
Oil price
1
Prognoseverfahren
1
Rapid evaluation method for inter-factory neighbourhoods
1
Scheduling problem
1
Scheduling-Verfahren
1
Sub-regional coevolution among multiple populations
1
Theorie
1
Theory
1
Turning point forecasting
1
WTI spot price
1
Wind farm optimization
1
Wind power potential
1
Ölpreis
1
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English
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Cheng, Fangzheng
1
Cui, Hanghao
1
Fan, Dandan
1
Fan, Tijun
1
Gao, Liang
1
Gao, Xiaoxia
1
Li, Shanling
1
Li, Xinyu
1
Lu, Lin
1
Yang, Hongxing
1
Zhang, Chunjiang
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Applied Energy
1
Energy economics
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International journal of production research
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ECONIS (ZBW)
2
RePEc
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1
Multi-population
genetic
algorithm
with greedy job insertion inter-factory neighbourhoods for multi-objective distributed hybrid flow-shop scheduling with unrelated-parallel machin...
Cui, Hanghao
;
Li, Xinyu
;
Gao, Liang
;
Zhang, Chunjiang
- In:
International journal of production research
62
(
2024
)
12
,
pp. 4427-4445
Persistent link: https://www.econbiz.de/10014547343
Saved in:
2
The prediction of oil price turning points with log-periodic power law and
multi-population
genetic
algorithm
Cheng, Fangzheng
;
Fan, Tijun
;
Fan, Dandan
;
Li, Shanling
- In:
Energy economics
72
(
2018
),
pp. 341-355
Persistent link: https://www.econbiz.de/10011972339
Saved in:
3
Study on offshore wind power potential and wind farm optimization in Hong Kong
Gao, Xiaoxia
;
Yang, Hongxing
;
Lu, Lin
- In:
Applied Energy
130
(
2014
)
C
,
pp. 519-531
optimized using the
Multi-Population
Genetic
Algorithm
(MPGA) which aims at getting a minimum cost of energy (COE) with a …
Persistent link: https://www.econbiz.de/10011041048
Saved in:
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