TY - JOUR
T1 - A novel search algorithm based on waterweeds reproduction principle for job shop scheduling problem
AU - Cheng, Lin
AU - Zhang, Qingzhen
AU - Tao, Fei
AU - Ni, Kun
AU - Cheng, Yang
N1 - Publisher Copyright:
© 2015, Springer-Verlag London.
PY - 2016/4/1
Y1 - 2016/4/1
N2 - Along with the mushroom development of new information technology, scheduling plays an increasing important role in manufacturing systems. A new search algorithm which imitates reproduction principle of waterweeds in searching for water sources is proposed for solving the job shop scheduling problems (JSSPs). Inspired by the swarm intelligence in waterweeds’ collaborative behavior and inheriting their strong survivability, the new waterweeds (WW) algorithm with few user-defined parameters and simple structure shows remarkable performance in solving continuous unconstrained optimization problems, which is proved by two experiments against five well-known benchmark functions. Furthermore, according to special needs of JSSPs solving, a series of modifications are introduced into original WW algorithm and the computational experiments on a set of problem instances indicate that the new discrete WW algorithm has competitive effectiveness and efficiency in comparison with other classical JSSPs solving methods in the literature. Successful application of WW algorithm in solving JSSPs illustrates its bright prospect in manufacturing field and other related optimization areas.
AB - Along with the mushroom development of new information technology, scheduling plays an increasing important role in manufacturing systems. A new search algorithm which imitates reproduction principle of waterweeds in searching for water sources is proposed for solving the job shop scheduling problems (JSSPs). Inspired by the swarm intelligence in waterweeds’ collaborative behavior and inheriting their strong survivability, the new waterweeds (WW) algorithm with few user-defined parameters and simple structure shows remarkable performance in solving continuous unconstrained optimization problems, which is proved by two experiments against five well-known benchmark functions. Furthermore, according to special needs of JSSPs solving, a series of modifications are introduced into original WW algorithm and the computational experiments on a set of problem instances indicate that the new discrete WW algorithm has competitive effectiveness and efficiency in comparison with other classical JSSPs solving methods in the literature. Successful application of WW algorithm in solving JSSPs illustrates its bright prospect in manufacturing field and other related optimization areas.
KW - Job shop scheduling problem
KW - Manufacturing scheduling
KW - Numerical optimization
KW - Swarm intelligence
KW - Waterweeds algorithm
KW - Waterweeds reproduction principle
UR - https://www.scopus.com/pages/publications/84948148095
U2 - 10.1007/s00170-015-8023-0
DO - 10.1007/s00170-015-8023-0
M3 - 文章
AN - SCOPUS:84948148095
SN - 0268-3768
VL - 84
SP - 405
EP - 424
JO - International Journal of Advanced Manufacturing Technology
JF - International Journal of Advanced Manufacturing Technology
IS - 1-4
ER -