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Solving a Business Process Optimization Issue With a Genetic Algorithm Coupled With Multi-Criteria Decision Analysis Method

Solving a Business Process Optimization Issue With a Genetic Algorithm Coupled With Multi-Criteria Decision Analysis Method
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Author(s): Nadir Mahammed (LabRI-SBA Laboratory, Ecole Supérieure en Informatique, Sidi Bel Abbès, Algeria)and Sidi Mohamed Benslimane (LabRI-SBA Laboratory, Ecole Supérieure en Informatique, Sidi Bel Abbès, Algeria)
Copyright: 2021
Volume: 11
Issue: 1
Pages: 24
Source title: International Journal of Organizational and Collective Intelligence (IJOCI)
Editor(s)-in-Chief: Victor Chang (Aston University, UK), Peng Liu (University of Kent)and Muthu Ramachandran (AI Tech and Forti5 Tech UK, United Kingdom)
DOI: 10.4018/IJOCI.2021010105

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Abstract

The addressed issue in the present work revolves around the area of business process management in general and in particular optimization. The problem involves the generation of optimized business process designs from a business process model in a multi-criteria optimization environment by appealing an evolutionary algorithm. Thus, the main contribution is to analyze the characteristics of using a multi-criteria decision-analysis method within a genetic algorithm in an issue of business process optimization. The experimental results clearly demonstrated that using a multi-criteria decision-analysis method helps considerably the production of qualitatively interesting alternative solutions in a reasonable period time regard-ing the problem complexity, which ultimately assists the decision maker to perform improved decision making

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