A Task Operation Model for Resource Allocation Optimization in Business Process Management

被引:28
|
作者
Huang, Zhengxing [1 ]
Lu, Xudong [1 ]
Duan, Huilong [1 ]
机构
[1] Zhejiang Univ, Coll Biomed Engn & Instrument Sci, Minist Educ, Key Lab Biomed Engn, Hangzhou 310058, Zhejiang, Peoples R China
来源
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS | 2012年 / 42卷 / 05期
关键词
Ant colony optimization (ACO); business process; optimization; resource allocation; task operation model (TOM); ANT COLONY OPTIMIZATION; GENETIC ALGORITHM; RULES;
D O I
10.1109/TSMCA.2012.2187889
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Resource allocation, as an integral part of business process management (BPM), is more widely acknowledged by its importance for process-aware information systems. Despite the industrial need for efficient and effective resource allocation in BPM, few scientifically-grounded approaches exist to support these initiatives. In this paper, a new approach of resource allocation optimization is proposed, built on the concepts that is part of an operation-oriented view on process optimization. Essentially, the proposed approach automatically generates a specific task operation model (TOM) for a particular business process. In addition, in order to support end users in making sensible resource allocations, an ant colony optimization-based algorithm is presented, which makes it possible to search an optimal task operation path on the generated TOM. This allows one to suggest how a business user should efficiently allocate resources to perform the tasks of a particular process case. The feasibility of the presented approach is demonstrated by a simulation experiment. The experimental results show that the proposed approach outperforms reasonable heuristic approaches to satisfy process performance goals, and it is possible to improve the current state of BPM.
引用
收藏
页码:1256 / 1270
页数:15
相关论文
共 50 条
  • [21] Optimization of Task Allocation for Resource-Constrained Swarm Robots
    Kang, Woosuk
    Jeong, Eunjin
    Shim, Sungjun
    Ha, Soonhoi
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2025, 22 : 3068 - 3085
  • [22] A Survey of Edge Computing Resource Allocation and Task Scheduling Optimization
    Xu, Xiaowei
    Ding, Han
    Wang, Jiayu
    Hua, Liang
    BIG DATA AND SECURITY, ICBDS 2023, PT II, 2024, 2100 : 125 - 135
  • [23] Resource Allocation and Task Offloading Joint Optimization for MEC in UDN
    Wei M.
    Geng S.
    Zhao X.
    Hu W.
    Fan J.
    Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications, 2023, 46 (02): : 50 - 56
  • [24] Optimization of Task Allocation for Resource-Constrained Swarm Robots
    Kang, Woosuk
    Jeong, Eunjin
    Shim, Sungjun
    Ha, Soonhoi
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2025, 22 : 3068 - 3085
  • [25] Particle model to optimize resource allocation and task assignment
    Shuai, Dianxun
    Shuai, Qing
    Dong, Yumin
    INFORMATION SYSTEMS, 2007, 32 (07) : 987 - 995
  • [26] Process Discovery in Business Process Management Optimization
    Dymora, Pawel
    Koryl, Maciej
    Mazurek, Miroslaw
    INFORMATION, 2019, 10 (09)
  • [27] Adaptive Service Configuration for Edge Resource Allocation in Business Process
    Sun, Mengyu
    Zhou, Zhangbing
    2020 IEEE WORLD CONGRESS ON SERVICES (SERVICES), 2020, : 37 - 40
  • [28] Research on Knowledge Resource Allocation Oriented Business Process Modeling
    Chen, Lei
    Zhan, Hongfei
    Yu, Junhe
    Jiang, Zhongren
    Lei, Chenjian
    ADVANCES IN ENGINEERING DESIGN AND OPTIMIZATION III, PTS 1 AND 2, 2012, 201-202 : 935 - 938
  • [29] A Business Model for Human Resource Management
    Kleinhempel, S.
    Nitchi, S. I.
    Rusu, L.
    PROCEEDINGS OF 2010 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION, QUALITY AND TESTING, ROBOTICS (AQTR 2010), VOLS. 1-3, 2010,
  • [30] On the Complexity of Resource Controllability in Business Process Management
    Zavatteri, Matteo
    Rizzi, Romeo
    Villa, Tiziano
    BUSINESS PROCESS MANAGEMENT WORKSHOPS, BPM 2020 INTERNATIONAL WORKSHOPS, 2020, 397 : 168 - 180