工程科学学报，第40卷，第7期：882-891,2018年7月 Chinese Journal of Engineering,Vol.40,No.7:882-891,July 2018 DOI:10.13374/j.issn2095-9389.2018.07.015;http://journals.ustb.edu.cn 领域QS与资源感知的物流服务动态优化组合方法 徐园园⑧，刘志中，贾宗璞 河南理工大学计算机科学与技术学院，焦作454000 ☒通信作者，E-mail:XUXUXu106@163.com 摘要为了提高物流服务优化组合的动态性、可靠性与用户满意度，本文提出了一种基于全局服务质量(quality of service, Q$)约束分解的能够感知领域质量与资源需求的物流服务优化组合方法.该研究工作首先把学习机制引入人工蜂群算法 (artificial bee colony algorithm,ABC),形成了具有自主学习能力的改进型人工蜂群算法(LABC):之后，应用学习人工蜂群算 法(LABC)将全局QS约束分解成每个物流子任务需要满足的局部QS约束，从而将QoS感知的物流服务优化组合这一全局 优化问题转化成以领域质量为依据的局部最优服务选择问题：其次，在物流服务流程执行的过程中，在感知物流任务节点对 资源需求的前提下，为每一个物流任务节点选择一个具有最优领域Q$的物流服务：与已有的研究工作相比，该方法能够实 现物流服务动态可靠的优化组合.最后，通过模拟实验验证了本文所提出的方法是可行有效的 关键词领域QoS;资源感知；物流服务组合；QS约束分解：人工蜂群算法 分类号TP393.09 Domain QoS and resource-aware logistics web service dynamic optimal composition XU Yuan-yuan,LIU Zhi-zhong,JIA Zong-pu College of Computer Science and Technology,Henan Polytechnic University,Jiaozuo 454000.China Corresponding author,E-mail:xuxuxul06@163.com ABSTRACT With the rapid development of service computing,cloud computing,internet of things,e-commerce,and modern logis- tics industry,cross-domain logistics services cooperation has become the main development trend of the modern logistics industry.The dynamic optimal composition of web services in logistics has become the key technology to create large and powerful logistics services based on the available logistics services of different companies that achieve seamless convergence of logistics services,satisfy user com- plex requirements,and realize the value addition.Recently,owing to the technologies of web services,cloud computing,and service sciences,an increasing number of logistics companies have registered themselves as logistics web service providers.The logistics serv- ices composition should satisfy the user's global QoS constraints and provide the best quality of service (QoS.)Currently,with the rapid development of cloud computing,e-commerce,service computing,and modern logistics industry,many logistics services are available on the network providing similar functions and different levels of QoS.These factors make the problem of determining the opti- mal composition of a logistics service a typical Np-hard problem.This study proposes a method to achieve the dynamic optimal composi- tion of domain QoS and resource-aware logistics services and to realize logistics services that are dynamic,offer quality of domain serv- ices,and are aware of resource requirements.First,the learning artificial bee colony algorithm (LABC)is proposed;LABC is applied to decompose the global QoS constraints into local QoS constraints that logistics task nodes must satisfy and to transform the global opti- mization problem of logistics service composition into a local optimal service selection problem.Second,during the process of logistics service process execution,for each task node,the logistics service with best domain QoS evaluation,which can satisfy the local QoS constraints and resource requirements,is chosen to achieve a high-quality dynamic logistics service and optimal composition of service. The results of simulation experiments show that the proposed method is feasible and effective. KEY WORDS domain QoS;resource-aware;logistics web services composition;QoS constraint decomposition;artificial bee colony 收稿日期：2017-10-09工程科学学报,第 40 卷,第 7 期:882鄄鄄891,2018 年 7 月 Chinese Journal of Engineering, Vol. 40, No. 7: 882鄄鄄891, July 2018 DOI: 10. 13374 / j. issn2095鄄鄄9389. 2018. 07. 015; http: / / journals. ustb. edu. cn 领域 QoS 与资源感知的物流服务动态优化组合方法 徐园园苣 , 刘志中, 贾宗璞 河南理工大学计算机科学与技术学院, 焦作 454000 苣通信作者, E鄄mail:xuxuxu106@ 163. com 摘 要 为了提高物流服务优化组合的动态性、可靠性与用户满意度,本文提出了一种基于全局服务质量( quality of service, QoS)约束分解的能够感知领域质量与资源需求的物流服务优化组合方法. 该研究工作首先把学习机制引入人工蜂群算法 (artificial bee colony algorithm, ABC),形成了具有自主学习能力的改进型人工蜂群算法(LABC);之后,应用学习人工蜂群算 法(LABC)将全局 QoS 约束分解成每个物流子任务需要满足的局部 QoS 约束,从而将 QoS 感知的物流服务优化组合这一全局 优化问题转化成以领域质量为依据的局部最优服务选择问题;其次,在物流服务流程执行的过程中,在感知物流任务节点对 资源需求的前提下,为每一个物流任务节点选择一个具有最优领域 QoS 的物流服务;与已有的研究工作相比,该方法能够实 现物流服务动态可靠的优化组合. 最后,通过模拟实验验证了本文所提出的方法是可行有效的. 关键词 领域 QoS; 资源感知; 物流服务组合; QoS 约束分解; 人工蜂群算法 分类号 TP393郾 09 收稿日期: 2017鄄鄄10鄄鄄09 Domain QoS and resource鄄aware logistics web service dynamic optimal composition XU Yuan鄄yuan 苣 , LIU Zhi鄄zhong, JIA Zong鄄pu College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000, China 苣Corresponding author, E鄄mail:xuxuxu106@ 163. com ABSTRACT With the rapid development of service computing, cloud computing, internet of things, e鄄commerce, and modern logis鄄 tics industry, cross鄄domain logistics services cooperation has become the main development trend of the modern logistics industry. The dynamic optimal composition of web services in logistics has become the key technology to create large and powerful logistics services based on the available logistics services of different companies that achieve seamless convergence of logistics services, satisfy user com鄄 plex requirements, and realize the value addition. Recently, owing to the technologies of web services, cloud computing, and service sciences, an increasing number of logistics companies have registered themselves as logistics web service providers. The logistics serv鄄 ices composition should satisfy the user爷s global QoS constraints and provide the best quality of service (QoS. ) Currently, with the rapid development of cloud computing, e鄄commerce, service computing, and modern logistics industry, many logistics services are available on the network providing similar functions and different levels of QoS. These factors make the problem of determining the opti鄄 mal composition of a logistics service a typical Np鄄hard problem. This study proposes a method to achieve the dynamic optimal composi鄄 tion of domain QoS and resource鄄aware logistics services and to realize logistics services that are dynamic, offer quality of domain serv鄄 ices, and are aware of resource requirements. First, the learning artificial bee colony algorithm (LABC) is proposed; LABC is applied to decompose the global QoS constraints into local QoS constraints that logistics task nodes must satisfy and to transform the global opti鄄 mization problem of logistics service composition into a local optimal service selection problem. Second, during the process of logistics service process execution, for each task node, the logistics service with best domain QoS evaluation, which can satisfy the local QoS constraints and resource requirements, is chosen to achieve a high鄄quality dynamic logistics service and optimal composition of service. The results of simulation experiments show that the proposed method is feasible and effective. KEY WORDS domain QoS; resource鄄aware; logistics web services composition; QoS constraint decomposition; artificial bee colony