DocumentCode
518063
Title
Notice of Retraction
A hybrid collaborative evolutionary method for Job Shop scheduling with parallel machines
Author
Zhou Ke ; Li Xiaodong ; Li Peng ; Gong Yongguang ; Wang Shoujun
Author_Institution
Dept. of Phys. & Inf. Eng., Jining Univ., Jining, China
Volume
4
fYear
2010
fDate
16-18 April 2010
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In order to solve the problem of Job Shop scheduling with parallel machines considering energy consumption, an optimization model of Job Shop scheduling with parallel machines was constructed, in which the energy consumption factor was included. The objective function of the model was to minimize the sum of completion time, number of tardiness workpieces and energy consumption. A hybrid collaborative evolutionary method was adopted to design the algorithm of Job Shop scheduling with parallel machines. In the algorithm a neighborhood-based evolutionary strategy was adopted to improve the population diversity. Finally, feasibility and effectiveness of the method are verified by an application case.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In order to solve the problem of Job Shop scheduling with parallel machines considering energy consumption, an optimization model of Job Shop scheduling with parallel machines was constructed, in which the energy consumption factor was included. The objective function of the model was to minimize the sum of completion time, number of tardiness workpieces and energy consumption. A hybrid collaborative evolutionary method was adopted to design the algorithm of Job Shop scheduling with parallel machines. In the algorithm a neighborhood-based evolutionary strategy was adopted to improve the population diversity. Finally, feasibility and effectiveness of the method are verified by an application case.
Keywords
energy consumption; evolutionary computation; job shop scheduling; optimisation; parallel machines; energy consumption factor; hybrid collaborative evolutionary method; job shop scheduling; neighborhood-based evolutionary strategy; optimization model; parallel machines; Algorithm design and analysis; Collaboration; Cost function; Energy consumption; Evolutionary computation; Genetic algorithms; Job shop scheduling; Optimal scheduling; Parallel machines; Production; Job Shop scheduling; energy consumption; hybrid collaborative evolutionary; neighborhood-based evolutionary;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-6347-3
Type
conf
DOI
10.1109/ICCET.2010.5485545
Filename
5485545
Link To Document