面向工业互联网平台的二维制造服务协作优化  

Dual-Dimensional Manufacturing Service Collaboration Optimization Toward Industrial Internet Platforms

作　　者：Shibao Pang Shunsheng Guo Xi Vincent Wang Lei Wang Lihui Wang 

机构地区：[1]School of Mechanical and Electrical Engineering,Wuhan University of Technology,Wuhan 430070,China [2]Hubei Digital Manufacturing Key Laboratory,Wuhan University of Technology,Wuhan 430070,China [3]Department of Production Engineering,KTH Royal Institute of Technology,Stockholm 10044,Sweden

出　　处：《Engineering》2023年第3期34-48,共15页工程（英文）

基　　金：the National Natural Science Foundation of China (51905396);the China Scholarship Council。

摘　　要：工业互联网平台被公认为智能制造的必要推动者,使物理制造资源得以虚拟化,并允许资源以服务的形式进行协作。作为平台的核心功能,制造服务协作优化致力于为制造任务提供高质量的服务协作解决方案。这种优化与任务的功能和数量要求密不可分,在编排服务时必须满足这些要求。然而,现有的制造服务协作优化方法主要关注服务之间针对功能需求的横向协作,很少考虑纵向协作来覆盖所需的数量。为了解决这一差距,本文提出了一种结合功能和数量协作的二维服务协作方法。首先,提出了一种描述服务的多粒度制造服务建模方法。在此基础上,建立了二维制造服务协同优化模型。在垂直维度上,多个功能等效的服务组成一个服务集群来完成一个子任务;在水平维度上,互补服务集群协作完成整个任务。服务的选择和所选服务的金额分配是模型中的关键问题。为了解决这个问题,设计了一种具有多个局部搜索算子的多目标模因算法。将该算法嵌入竞争机制来动态调整本地搜索算子的选择概率。实验结果表明,与常用算法相比,该算法在收敛性、解质量和综合度量方面具有优势。An Industrial Internet platform is acknowledged to be a requisite promoter for smart manufacturing,enabling physical manufacturing resources to be virtualized and permitting resources to collaborate in the form of services.As a central function of the platform,manufacturing service collaboration optimiza-tion is dedicated to establishing high-quality service collaboration solutions for manufacturing tasks.Such optimization is inseparable from the functional and amount requirements of a task,which must be satisfied when orchestrating services.However,existing manufacturing service collaboration opti-mization methods mainly focus on horizontal collaboration among services for functional demands and rarely consider vertical collaboration to cover the needed amounts.To address this gap,this paper proposes a dual-dimensional service collaboration methodology that combines functional and amount collaboration.First,a multi-granularity manufacturing service modeling method is presented to describe services.On this basis,a dual-dimensional manufacturing service collaboration optimization(DMSCO)model is formulated.In the vertical dimension,multiple functionally equivalent services form a service cluster to fulfill a subtask;in the horizontal dimension,complementary service clusters collaborate for the entire task.Service selection and amount distribution to the selected services are critical issues in the model.To solve the problem,a multi-objective memetic algorithm with multiple local search opera-tors is tailored.The algorithm embeds a competition mechanism to dynamically adjust the selection probabilities of the local search operators.The experimental results demonstrate the superiority of the algorithm in terms of convergence,solution quality,and comprehensive metrics,in comparison with commonly used algorithms.

关 键 词：Manufacturing service collaboration Service optimal selection Service granularity Industrial Internet platform 

分 类 号：TP393.09[自动化与计算机技术—计算机应用技术]