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Información general |
| Autor |
Zhang, Rui |
| Publicado |
InTech Open Access Publisher, 2013
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| Edición |
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| ISBN |
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| Abstract |
A decomposition-based optimization algorithm
is proposed for solving large job shop scheduling problems
with the objective of minimizing the maximum lateness.
First, we use the constraint propagation theory to
derive the orientation of a portion of disjunctive arcs.
Then we use a simulated annealing algorithm to find
a decomposition policy which satisfies the maximum
number of oriented disjunctive arcs. Subsequently, each
subproblem (corresponding to a subset of operations as
determined by the decomposition policy) is successively
solved with a simulated annealing algorithm, which leads
to a feasible solution to the original job shop scheduling
problem. Computational experiments are carried out for
adapted benchmark problems, and the results show the
proposed algorithm is effective and efficient in terms of
solution quality and time performance. |
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International Journal of Advanced Robotic Systems
Autor: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Publicado: 2004
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