Abstract
In this paper, a research was carried out on the problem of evolutionary multi objective business process optimization. It does involve (i) to construct feasible business process designs with optimum attributes, and (ii) to classify the obtained solutions using a simple and scientific approach understandable by the decision maker. The business process evolutionary multi objective optimization (BPMOO) approach involves the generation of a series of diverse optimized business process designs for the same process requirements using an evolutionary algorithm (EA). The work presented in this paper is aimed to investigate the benefits that come from the utilization of multiple-criteria decision analysis methods (MCDA) with an evolutionary multi objective optimization algorithms (EMOA) execution process. The experimental results clearly bring that the proposed optimization Framework is capable of producing an acceptable number of optimized design alternatives to simplify the decision maker’s choice of solutions in a reasonable runtime.
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Mahammed, N., Benslimane, S.M., Ouldkradda, A., Fahsi, M. (2019). Evolutionary Multi Optimization Business Process Designs Using MR-Sort NSGAII. In: Renault, É., Boumerdassi, S., Bouzefrane, S. (eds) Mobile, Secure, and Programmable Networking. MSPN 2018. Lecture Notes in Computer Science(), vol 11005. Springer, Cham. https://doi.org/10.1007/978-3-030-03101-5_3
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