TY - JOUR
T1 - Solving a class of job-shop scheduling problem based on improved BPSO algorithm
AU - Fan, Kun
AU - Zhang, Ren Qian
AU - Xia, Guo Ping
PY - 2007/11
Y1 - 2007/11
N2 - Analyzing the special job shop scheduling problem of a large-scale machine shop, considering workers' operational qualification and characteristics of discretely concurrent production, a novel mathematical model has been proposed to meet actual production. In addition, an improved Binaiy Particle Swarm Optimizer (BPSO) algorithm has been developed for solving the problem how to arrange m workers to process n structures, in order to optimize the minimum completion time of the jobs. In this improved BPSO, a new method of making initial particles has been presented for searching optimum particle in the feasible dimensional problem space. Besides, importing memory base, modifying Sig function and considering constraint condition have used in algorithm for making updated particles to meet the constraint equation of mathematical model. Algorithm examples research demonstrates that the improved BPSO algorithm is effective and can achieve good results. Moreover, the mathematical model has wide application in discrete manufacture.
AB - Analyzing the special job shop scheduling problem of a large-scale machine shop, considering workers' operational qualification and characteristics of discretely concurrent production, a novel mathematical model has been proposed to meet actual production. In addition, an improved Binaiy Particle Swarm Optimizer (BPSO) algorithm has been developed for solving the problem how to arrange m workers to process n structures, in order to optimize the minimum completion time of the jobs. In this improved BPSO, a new method of making initial particles has been presented for searching optimum particle in the feasible dimensional problem space. Besides, importing memory base, modifying Sig function and considering constraint condition have used in algorithm for making updated particles to meet the constraint equation of mathematical model. Algorithm examples research demonstrates that the improved BPSO algorithm is effective and can achieve good results. Moreover, the mathematical model has wide application in discrete manufacture.
KW - Binary Particle Swarm Optimizer (BPSO)
KW - Job shop scheduling
KW - Structure
UR - https://www.scopus.com/pages/publications/37749036822
U2 - 10.1016/s1874-8651(08)60067-8
DO - 10.1016/s1874-8651(08)60067-8
M3 - 文章
AN - SCOPUS:37749036822
SN - 1000-6788
VL - 27
SP - 111
EP - 117
JO - Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice
JF - Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice
IS - 11
ER -