Abstract: The Industrial Internet combines industrial systems with Internet techniques to significantly improve production efficiency and reduce cost by cooperating with intelligent devices.Under the Industrial Internet environment,a production process usually consists of multiple tasks,and one or more types of product factors are needed to finish a task.Thus,the service composition under industrial application is complex and challenging compared with traditional service composition under the Internet environment.To solve the problem of service composition for production factor resource under Industrial Internet,the key concepts was defined,and was modeled as a multi-objective optimization problem.To derive the optimal service composition solution,a hybrid optimization algorithm was proposed by combining the advantages of Teaching Learning Based Optimization algorithm(TLBO)and Tabu Search algorithm(TS),which named TLBO-TS.A series of extended experiments was conducted,and the result showed that the TLBO-TS method had better optimality.

Key words: industrial Internet, production factor resource, service composition, hybrid algorithm, multi-objective optimization

摘要： 工业互联网将工业系统与互联网技术相结合,通过与智能设备的配合显著提高生产效率、降低生产成本。在工业互联网环境下,一个生产过程通常由多个子任务组成,同时一个子任务的完成需要多个或多种生产要素资源。与互联网环境下的传统服务组合相比,工业应用下的服务组合更为复杂且具有挑战性。为解决工业互联网环境下生产要素资源的服务组合优化问题,本文定义了该问题的关键概念,并将其建模为一个多目标优化问题。其次,为得到最优的服务组合解,结合教学优化算法(TLBO)和禁忌搜索算法(TS)的优点,提出一种混合的多目标优化算法,称为TLBO-TS。最后,进行了一系列的扩展实验。实验结果验证了TLBO-TS算法的优越性。

关键词: 工业互联网, 生产要素资源, 服务组合, 混合算法, 多目标优化