DocumentCode :
3576511
Title :
A modified genetic algorithm for precedence constrained operation sequencing problem in process planning
Author :
Yuliang Su ; Xuening Chu ; Dongping Chen ; Dexin Chu
Author_Institution :
Sch. of Mech. Eng., Shanghai Jiao Tong Univ., Shanghai, China
fYear :
2014
Firstpage :
84
Lastpage :
88
Abstract :
Precedence constrained operation sequencing problem (PCOSP) is concerned with selection of feasible and efficient operation sequence with minimal machining cost in process planning. Traditional genetic algorithm (GA) generates solution sequence by using randomly selection and insertion of operations, which will break the precedence constraints between operations. The additional fixing approaches for the infeasible solutions will result in low efficiency. Some modified GAs could generate feasible solutions but have premature convergence problem when facing complicated precedence constraints. To overcome the shortcomings, this paper proposed a modified GA that use an edge selection based chromosome encoding approach to make sure all the precedence constraints are met in every step. The experiment illustrates that the proposed GA has superiority in finding optimal or near optimal solution.
Keywords :
genetic algorithms; machining; process planning; PCOSP; edge selection based chromosome encoding approach; genetic algorithm; minimal machining cost; precedence constrained operation sequencing problem; premature convergence problem; process planning; random operation insertion; random operation selection; Biological cells; Cutting tools; Encoding; Genetic algorithms; Indexes; Machine tools; Mathematical model; Process planning; genetic algorithm; precedence constrained operation sequencing problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Engineering and Engineering Management (IEEM), 2014 IEEE International Conference on
Type :
conf
DOI :
10.1109/IEEM.2014.7058605
Filename :
7058605
Link To Document :
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