Multi-objective Approach for Non-dominated Solutions in Digital Twin
Gregor Papa, Peter KoroÅ¡ec
Journal of Data Processing, Vol. 8, No. 4, 2018.
DOI: 
Link: http://www.dline.info/jdp/fulltext/v8n4/jdpv8n4_2.pdf
Abstract:
The value of Digital twins in the smart world has been realized in the recent years. In the information technology
there is a strong move towards the digital twin currently. In this work we introduce an initial step to upgrade simulations
to digital twins to enhance the productivity even further. The multi-objective optimisation approach is important in achieving
high efficiency of production scheduling. The goal of the optimization is to end a production schedule that satisfies
different, contradictory production constraints. We take a simulation tool that was used by a memetic version of the Indicator-
Based Evolutionary Algorithm with customized reproduction operators and local search procedures to end a set of feasible,
non-dominated solutions and analyse the required steps to achieve a digital twin. We show that with a multi-objective
approach that is able to find high-quality solutions and flexibility of many â€œequalâ€ solutions, the digital twin becomes a
powerful tool for a decision maker.