Article ID: | iaor20134951 |
Volume: | 25 |
Issue: | 3 |
Start Page Number: | 543 |
End Page Number: | 559 |
Publication Date: | Jun 2013 |
Journal: | INFORMS Journal on Computing |
Authors: | Chu Chao-Hsien, Kumar Akhil, Yao Wen |
Keywords: | penalty functions, mixed integer programming |
An adaptive process management system (APMS) allows for flexible, dynamic, and even ad hoc adaptation of processes based on case data, context, and events. These processes may arise in various domains such as business, healthcare, etc. In knowledge‐intensive environments, it is important that APMS technology ensures error‐free process execution and compliance with semantic constraints. However, most process design tools handle only syntactic constraints. This restricts their value in real‐world applications considerably. This paper proposes a novel approach to check the compliance of process models against semantic constraints and the validity of process change operations using mixed‐integer programming (MIP). The MIP formulation allows us to describe existential, dependency, ordering, and various other relationships among tasks along with business policies in a standard way. In addition to incorporating the semantic constraint specifications into an MIP formulation, we introduce three novel ideas in this paper: (1) the notion of