Hybrid business process modeling for the optimization of outcome data

被引:10
|
作者
Parody, Luisa [1 ]
Teresa Gomez-Lopez, Maria [1 ]
Gasca, Rafael M. [1 ]
机构
[1] Univ Seville, Dept Languages & Comp Syst, Seville, Spain
关键词
Hybrid model; Business process; Constraint programming; Data optimization; RECOMMENDATIONS; CONSTRAINTS; EXECUTION; LANGUAGES; ISSUE;
D O I
10.1016/j.infsof.2015.10.007
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Context: Declarative business processes are commonly used to describe permitted and prohibited actions in a business process. However, most current proposals of declarative languages fail in three aspects: (1) they tend to be oriented only towards the execution order of the activities; (2) the optimization is oriented only towards the minimization of the execution time or the resources used in the business process; and (3) there is an absence of capacity of execution of declarative models in commercial Business Process Management Systems. Objective: This contribution aims at taking into account these three aspects, by means of: (1) the formalization of a hybrid model oriented towards obtaining the outcome data optimization by combining a data-oriented declarative specification and a control-flow-oriented imperative specification; and (2) the automatic creation from this hybrid model to an imperative model that is executable in a standard Business Process Management System. Method: An approach, based on the definition of a hybrid business process, which uses a constraint programming paradigm, is presented. This approach enables the optimized outcome data to be obtained at runtime for the various instances. Results: A language capable of defining a hybrid model is provided, and applied to a case study. Likewise, the automatic creation of an executable constraint satisfaction problem is addressed, whose resolution allows us to attain the optimized outcome data. A brief computational study is also shown. Conclusion: A hybrid business process is defined for the specification of the relationships between declarative data and control-flow imperative components of a business process. In addition, the way in which this hybrid model automatically creates an entirely imperative model at design time is also defined. The resulting imperative model, executable in any commercial Business Process Management System, can obtain, at execution time, the optimized outcome data of the process. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:140 / 154
页数:15
相关论文
共 50 条
  • [1] Business process modeling supporting personalized optimization
    School of Software, Sun Yat-Sen University, Guangzhou 510006, China
    不详
    不详
    Jisuanji Jicheng Zhizao Xitong, 2013, 1 (137-145):
  • [2] A hybrid model for business process event and outcome prediction
    Le, Mai
    Gabrys, Bogdan
    Nauck, Detlef
    EXPERT SYSTEMS, 2017, 34 (05)
  • [3] Multidimensional data modeling for business process analysis
    Mansmann, Svetlana
    Neumuth, Thomas
    Scholl, Marc H.
    CONCEPTUAL MODELING - ER 2007, PROCEEDINGS, 2007, 4801 : 23 - +
  • [4] Hybrid modeling and optimization of acetylene hydrogenation process
    Ye Z.
    Zhou H.
    Rao D.
    Huagong Xuebao/CIESC Journal, 2019, 70 (02): : 496 - 507
  • [5] Business Process Modeling Languages and their Data Representation Capabilities
    Teixeira, Julian
    Santos, Maribel Yasmina
    Machado, Ricardo J.
    2018 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS (IS), 2018, : 685 - 691
  • [6] Data quality management using business process modeling
    Bagchi, Sugato
    Bai, Xue
    Kalagnanam, Jayant
    2006 IEEE INTERNATIONAL CONFERENCE ON SERVICES COMPUTING, PROCEEDINGS, 2006, : 398 - +
  • [7] Data Protection Risk Modeling into Business Process Analysis
    Goncalves, Antonio
    Correia, Anacleto
    Cavique, Luis
    COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2017, PT I, 2017, 10404 : 667 - 676
  • [8] A hybrid approach for aspect-oriented business process modeling
    Jalali, Amin
    Maggi, Fabrizio Maria
    Reijers, Hajo A.
    JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS, 2018, 30 (08)
  • [9] Modeling and Optimization for Collaborative Business Process Towards IoT Applications
    Cheng, Yongyang
    Zhao, Shuai
    Cheng, Bo
    Hou, Shoulu
    Shi, Yulong
    Chen, Junliang
    MOBILE INFORMATION SYSTEMS, 2018, 2018
  • [10] Optimization method based on big data in business process management
    Li, Tingshun
    Xiong, Li
    Dong, Aiqiang
    Liu, Ze-San
    Tan, Wen
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2019, 22 (Suppl 3): : S5357 - S5365