A service composition method using improved hybrid teaching learning optimization algorithm in cloud manufacturing

Abstract In the cloud manufacturing process, service composition can combine a single into complex to meet task requirements. An efficient strategy is crucial, as it affects efficiency of resource and capacity sharing in system. However, face large-scale environment, existing methods have problems slow convergence instability. To solve above, we propose an improved optimization method, named improved-TC. Specifically, are inspired by horizontal crossover CSO hybrid-TC teaching phase, Hybrid-TC proposed our previous work, which hybrid teaching-learning-based algorithm (TLBO) crisscross (CSO). Improved-TC improvement on learning phase algorithm, change search method one-dimensional search, thereby some dimensions population that trapped local optimum chance jump out iteration. Experiments show has faster speed more stability environments.