Advertisement
Published in:
2015 | OriginalPaper | Chapter
Generating Business Process Recommendations with a Population-Based Meta-Heuristic
Authors : Steven Mertens, Frederik Gailly, Geert Poels
Published in: Business Process Management Workshops
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Abstract
In order to provide both guidance and flexibility to users during process execution, recommendation systems have been proposed. Existing recommendation systems mainly focus on offering recommendation according to the process optimization goals (time, cost…). In this paper we offer a new approach that primarily focuses on maximizing the flexibility during execution. This means that by following the recommendations, the user retains maximal flexibility to divert from them later on. This makes it possible to handle (possibly unknown) emerging constraints during execution. The main contribution of this paper is an algorithm that uses a declarative process model to generate a set of imperative process models that can be used to generate recommendations.