Ensuring Flexible Process Compliance with Semantic Constraints using 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 tec...

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Main Authors: KUMAR, Akhil, YAO, Wen, CHU, Chao-Hsien
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Language:English
Published: Institutional Knowledge at Singapore Management University 2012
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Online Access:https://ink.library.smu.edu.sg/sis_research/2234
http://dx.doi.org/10.1287/ijoc.1120.0520
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spelling sg-smu-ink.sis_research-32342014-06-24T09:36:18Z Ensuring Flexible Process Compliance with Semantic Constraints using Mixed-Integer Programming KUMAR, Akhil YAO, Wen CHU, Chao-Hsien 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 degree of compliance of processes to constraints based on a penalty function, 2 the concepts of full and partial validity of change operations, and 3 the idea of compliance by compensation. Thus, compensation operations derived from compliance degree can transform a noncompliant process into a compliant one both at design and execution time. We illustrate our approach in the context of a healthcare workflow as a way to reduce medical errors and argue that it is more elegant and superior to a pure logic-based approach. Complex scenarios with multiple concurrent processes and constraints across them for a single patient are also considered. 2012-09-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/2234 info:doi/10.1287/ijoc.1120.0520 http://dx.doi.org/10.1287/ijoc.1120.0520 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University adaptive process management systems semantic constraints compliance change operations mixed integer programming Computer Sciences Management Information Systems
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic adaptive process management systems
semantic constraints
compliance
change operations
mixed integer programming
Computer Sciences
Management Information Systems
spellingShingle adaptive process management systems
semantic constraints
compliance
change operations
mixed integer programming
Computer Sciences
Management Information Systems
KUMAR, Akhil
YAO, Wen
CHU, Chao-Hsien
Ensuring Flexible Process Compliance with Semantic Constraints using Mixed-Integer Programming
description 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 degree of compliance of processes to constraints based on a penalty function, 2 the concepts of full and partial validity of change operations, and 3 the idea of compliance by compensation. Thus, compensation operations derived from compliance degree can transform a noncompliant process into a compliant one both at design and execution time. We illustrate our approach in the context of a healthcare workflow as a way to reduce medical errors and argue that it is more elegant and superior to a pure logic-based approach. Complex scenarios with multiple concurrent processes and constraints across them for a single patient are also considered.
format text
author KUMAR, Akhil
YAO, Wen
CHU, Chao-Hsien
author_facet KUMAR, Akhil
YAO, Wen
CHU, Chao-Hsien
author_sort KUMAR, Akhil
title Ensuring Flexible Process Compliance with Semantic Constraints using Mixed-Integer Programming
title_short Ensuring Flexible Process Compliance with Semantic Constraints using Mixed-Integer Programming
title_full Ensuring Flexible Process Compliance with Semantic Constraints using Mixed-Integer Programming
title_fullStr Ensuring Flexible Process Compliance with Semantic Constraints using Mixed-Integer Programming
title_full_unstemmed Ensuring Flexible Process Compliance with Semantic Constraints using Mixed-Integer Programming
title_sort ensuring flexible process compliance with semantic constraints using mixed-integer programming
publisher Institutional Knowledge at Singapore Management University
publishDate 2012
url https://ink.library.smu.edu.sg/sis_research/2234
http://dx.doi.org/10.1287/ijoc.1120.0520
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