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Prozessmanagement
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genetic algorithm
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hybrid flow shop scheduling
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mixed integer linear programming
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Computers & operations research : and their applications to problems of world concern ; an international journal
2
International journal of production research
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Journal of the Operational Research Society
1
Multi-objective evolutionary optimisation for product design and manufacturing
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ECONIS (ZBW)
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Mathematical modeling and evolutionary algorithm-based approach for integrated process planning and scheduling
Li, Xinyu
;
Gao, Liang
;
Shao, Xinyu
;
Zhang, Chaoyong
; …
- In:
Computers & operations research : and their …
37
(
2010
)
4
,
pp. 656-667
Persistent link: https://www.econbiz.de/10003944419
Saved in:
2
Integration of process planning and scheduling : a modified genetic algorithm-based approach
Shao, Xinyu
;
Li, Xinyu
;
Gao, Liang
;
Zhang, Chaoyong
- In:
Computers & operations research : and their …
36
(
2009
)
6
,
pp. 2082-2096
Persistent link: https://www.econbiz.de/10003828425
Saved in:
3
Intelligent optimisation for integrated process planning and scheduling
Li, Weidong
;
Wang, Lihui
;
Li, Xinyu
;
Gao, Liang
- In:
Multi-objective evolutionary optimisation for product …
,
(pp. 305-324)
.
2011
Persistent link: https://www.econbiz.de/10009311568
Saved in:
4
Integrated process planning and scheduling using an imperialist competitive algorithm
Lian, Kunlei
;
Zhang, Chaoyong
;
Gao, Liang
;
Li, Xinyu
- In:
International journal of production research
50
(
2012
)
15
,
pp. 4326-4343
Persistent link: https://www.econbiz.de/10009621247
Saved in:
5
Two novel MILP models with different flexibilities for solving integrated process planning and scheduling problems
Liu, Qihao
;
Li, Xinyu
;
Gao, Liang
;
Fan, Jiaxin
- In:
Journal of the Operational Research Society
74
(
2023
)
9
,
pp. 1955-1967
Persistent link: https://www.econbiz.de/10014336416
Saved in:
6
More MILP models for integrated process planning and scheduling
Jin, Liangliang
;
Tang, Qiuhua
;
Zhang, Chaoyong
;
Shao, Xinyu
- In:
International journal of production research
54
(
2016
)
13/14
,
pp. 4387-4402
Persistent link: https://www.econbiz.de/10011508704
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