TY - JOUR
T1 - Research on networked manufacturing unit selection based on genetic algorithm
AU - Yao, Chang Feng
AU - Zhang, Ding Hua
AU - Peng, Wen Li
PY - 2004/12
Y1 - 2004/12
N2 - To solve physical manufacturing unit (PMU) selection question in the networked cooperative manufacturing process, an improved algorithm based on GA was proposed. Integer coding method was adopted in the algorithm, and a chromosome represented an executive manufacturing process (EMP). In order to obtain the optimized EMP, the objective function was constructed according to the optimizing objective, namely the total running costs, time and machining quality (CTQ). During seeking the answer to this question, the CTQ's value of each chromosome and the influence degree to decision making due to the CTQ's non-standardization were calculated in every generation. Through making using of the influence degree coefficient, the relative membership degree of each chromosome to the least total running cost, time and the best machining quality was calculated. Then, the relative fitness function was set up and its value was computed by using the relative membership degree to reduce the influence degree of CTQ's non-standardization to decision-making. At last, an example was given to prove the algorithm's feasibility and validity.
AB - To solve physical manufacturing unit (PMU) selection question in the networked cooperative manufacturing process, an improved algorithm based on GA was proposed. Integer coding method was adopted in the algorithm, and a chromosome represented an executive manufacturing process (EMP). In order to obtain the optimized EMP, the objective function was constructed according to the optimizing objective, namely the total running costs, time and machining quality (CTQ). During seeking the answer to this question, the CTQ's value of each chromosome and the influence degree to decision making due to the CTQ's non-standardization were calculated in every generation. Through making using of the influence degree coefficient, the relative membership degree of each chromosome to the least total running cost, time and the best machining quality was calculated. Then, the relative fitness function was set up and its value was computed by using the relative membership degree to reduce the influence degree of CTQ's non-standardization to decision-making. At last, an example was given to prove the algorithm's feasibility and validity.
KW - Fitness function
KW - Genetic algorithm
KW - Influence degree coefficient
KW - Manufacturing unit
KW - Relative membership degree
UR - http://www.scopus.com/inward/record.url?scp=14344259519&partnerID=8YFLogxK
M3 - 文章
AN - SCOPUS:14344259519
SN - 1006-5911
VL - 10
SP - 1555
EP - 1560
JO - Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS
JF - Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS
IS - 12
ER -