A framework for service enterprise workflow simulation with multi-agents cooperation

Process dynamic modelling for service business is the key technique for Service-Oriented information systems and service business management, and the workflow model of business processes is the core part of service systems. Service business workflow simulation is the prevalent approach to be used for analysis of service business process dynamically. Generic method for service business workflow simulation is based on the discrete event queuing theory, which is lack of flexibility and scalability. In this paper, we propose a service workflow-oriented framework for the process simulation of service businesses using multi-agent cooperation to address the above issues. Social rationality of agent is introduced into the proposed framework. Adopting rationality as one social factor for decision-making strategies, a flexible scheduling for activity instances has been implemented. A system prototype has been developed to validate the proposed simulation framework through a business case study.

[1]  Hooshang M. Beheshti,et al.  Improving productivity and firm performance with enterprise resource planning , 2010, Enterp. Inf. Syst..

[2]  Huimin Liu,et al.  Modelling and analysis techniques for cross‐organizational workflow systems , 2009 .

[3]  Colin Potts,et al.  A CASE tool supported methodology for the design of multi-agent systems , 2002 .

[4]  Nicolas Guelfi,et al.  Modelling dependable collaborative time-constrained business processes , 2010, Enterp. Inf. Syst..

[5]  Mario Piattini,et al.  Generating event logs from non-process-aware systems enabling business process mining , 2011, Enterp. Inf. Syst..

[6]  Andrew P. Martin,et al.  SWSpec: The Requirements Specification Language in Service Workflow Environments , 2012, IEEE Transactions on Industrial Informatics.

[7]  Aniruddha S. Gokhale,et al.  FORMS: Feature-Oriented Reverse Engineering-based Middleware Specialization for Product-Lines , 2011, J. Softw..

[8]  Michael Grüninger,et al.  PSL: A semantic domain for flow models , 2005, Software & Systems Modeling.

[9]  Meg Fryling,et al.  Estimating the impact of enterprise resource planning project management decisions on post-implementation maintenance costs: a case study using simulation modelling , 2010, Enterp. Inf. Syst..

[10]  John Ryan,et al.  Process modeling for simulation , 2006, Comput. Ind..

[11]  Li D. Xu Information architecture for supply chain quality management , 2011 .

[12]  Lei Ren,et al.  Cloud manufacturing: a new manufacturing paradigm , 2014, Enterp. Inf. Syst..

[13]  Nan Niu,et al.  A case study of exploiting enterprise resource planning requirements , 2011, Enterp. Inf. Syst..

[14]  Kurt Maly,et al.  Scheduling-Capable Autonomic Manager for Policy Based IT Change Management System , 2008, 2008 12th International IEEE Enterprise Distributed Object Computing Conference.

[15]  WenAn Tan,et al.  A Business Process Intelligence System for Enterprise Process Performance Management , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[16]  Lida Xu,et al.  Enterprise Systems: State-of-the-Art and Future Trends , 2011, IEEE Transactions on Industrial Informatics.

[17]  Panagiota N. Panagopoulou,et al.  Rationality authority for provable rational behavior , 2011, PODC '11.

[18]  Wei Xu,et al.  A methodology toward manufacturing grid-based virtual enterprise operation platform , 2010, Enterp. Inf. Syst..

[19]  Maria Ozanira da Silva e. Silva Constructing a Participatory Approach for the Evaluation of Social Policies and Programmes , 2011 .

[20]  Wei Tan,et al.  Dynamic workflow model fragmentation for distributed execution , 2007, Comput. Ind..

[21]  Nicholas R. Jennings,et al.  Towards a social level characterisation of socially responsible agents , 1997, IEE Proc. Softw. Eng..

[22]  WenAn Tan,et al.  Role-oriented process-driven enterprise cooperative work using the combined rule scheduling strategies , 2008, Inf. Syst. Frontiers.

[23]  Chien-wen Shen,et al.  Business process re-engineering in the logistics industry: a study of implementation, success factors, and performance , 2010, Enterp. Inf. Syst..

[24]  Jan Holmström,et al.  Agent-based model for managing composite product information , 2006, Comput. Ind..

[25]  Jianmin Zhao,et al.  A methodology for dynamic enterprise process performance evaluation , 2007, Comput. Ind..

[26]  Hong Wang,et al.  Study on the evolutionary optimisation of the topology of network control systems , 2010, Enterp. Inf. Syst..