@Article{cmc.2020.011149,
AUTHOR = {Bin Xu, Yong Tang, Yi Zhu, Wenqing Yan, Cheng He, Jin Qi},
TITLE = {Bilateral Collaborative Optimization for Cloud Manufacturing Service},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {64},
YEAR = {2020},
NUMBER = {3},
PAGES = {2031--2042},
URL = {http://www.techscience.com/cmc/v64n3/39474},
ISSN = {1546-2226},
ABSTRACT = {Manufacturing service composition of the supply side and scheduling of the
demand side are two important components of Cloud Manufacturing, which directly 
affect the quality of Cloud Manufacturing services. However, the previous studies on the
two components are carried out independently and thus ignoring the internal relations and 
mutual constraints. Considering the two components on both sides of the supply and the
demand of Cloud Manufacturing services at the same time, a Bilateral Collaborative 
Optimization Model of Cloud Manufacturing (BCOM-CMfg) is constructed in this paper. 
In BCOM-CMfg, to solve the manufacturing service scheduling problem on the supply 
side, a new efficient manufacturing service scheduling strategy is proposed. Then, as the 
input of the service composition problem on the demand side, the scheduling strategy is 
used to build the BCOM-CMfg. Furthermore, the Cooperation Level (CPL) between 
services is added as an evaluation index in BCOM-CMfg, which reveals the importance 
of the relationship between services. To improve the quality of manufacturing services 
more comprehensively. Finally, a Self-adaptive Multi-objective Pigeon-inspired 
Optimization algorithm (S-MOPIO) is proposed to solve the BCOM-CMfg. Simulation 
results show that the BCOM-CMfg model has advantages in reliability and cost and SMOPIO can solve BCOM-CMfg effectively.},
DOI = {10.32604/cmc.2020.011149}
}