Multi-Criteria Decision Making for Optimal Configuration of Business Process Model Families

Ramo Šendelj, Ivana Ognjanović

Abstract


Business process model families (BPMF) provide collective representation of business processes that can be defined for a target domain of interest. They enable rapid development of appropriate business processes by quick BPMF configuration based on the stakeholders’ needs and preferences. In this paper we propose a novel framework for user-centric quality-driven configuration of business process model families capturing different kinds of non-functional preferences and solving the optimal BPMFs configuration problem. Focusing on the following key elements: Analytic Hierarchy Process (AHP), and its extension known as CS-AHP, Fuzzy logic and Genetic Algorithms; the framework maximizes the degree of satisfaction of defined non-functional preferences while simultaneously preserving the behavioural correctness of each derived business process. Furthermore, we provide extensive analyses of the proposed framework from three different perspectives: accuracy assessment, analysis of the impact of different variability and uncertainty elements, and comparison with respect to the published literature. Empirical analyses in this paper indicated that the proposed approach outperforms competitors.

DOI: http://dx.doi.org/10.5755/j01.itc.47.3.18652


Keywords


Business Process Model families; Multi-criteria decision making; CS-AHP; Genetic algorithm; Fuzzy logic

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Print ISSN: 1392-124X 
Online ISSN: 2335-884X