Optimizing process model redesign

Akhil Kumar, Paronkasom Indradat

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In recent years there has been considerable interest in business process redesign. A process model may be redesigned by combining various tasks and services according to best practices so as to satisfy predefined business rules and constraints to achieve a specific purpose. This purpose may be stated in terms of functional goals (such as desired or acceptable process behavior) and non-functional goals like cost, time and quality of service. There are many ways to redesign a process instance by applying improvements such as: making a task optional, replacing a task by another faster task (or service), task postponement, task combination, task splitting, task restructuring, etc. Given many such alternatives, there is no systematic way of evaluating their costs and benefits, and the tradeoffs among them. We describe a novel approach based on a formal model to optimize the “benefits” or net effects of a redesign with respect to a baseline design and show how it can be used to evaluate and compare alternative models at both design and run time.

Original languageEnglish (US)
Title of host publicationService-Oriented Computing - 14th International Conference, ICSOC 2016, Proceedings
EditorsSamir Tata, Eleni Stroulia, Sami Bhiri, Quan Z. Sheng
PublisherSpringer Verlag
Pages39-54
Number of pages16
ISBN (Print)9783319462943
DOIs
StatePublished - Jan 1 2016
Event14th International Conference on Service-Oriented Computing, ICSOC 2016 - Banff, Canada
Duration: Oct 10 2016Oct 13 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9936 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other14th International Conference on Service-Oriented Computing, ICSOC 2016
CountryCanada
CityBanff
Period10/10/1610/13/16

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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