Abstract
Nowadays, the most real-life problems are multi-objective or many objective in nature, which needs to be optimized to give a promising solution to the user. But the problem comes when we have to select the most significant solution from the large solution space. As a result, by applying genetic algorithm, we get a front which contains number of optimal solutions named as Pareto-optimal front. To select the most significant solution from a number of optimal solutions is a very difficult task as all solutions are nondominated to each other. The decision maker has to select a single solution. In this paper, we have shown an improvement on NSGA-II in order to select quickly the most significant and acceptable solution by the decision maker.
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De, P.S., Mishra, B.S.P. (2015). An Improvement on NSGA-II for Finding Fast the Better Optimal Solution in Multi-objective Optimization Problem. In: Jain, L., Patnaik, S., Ichalkaranje, N. (eds) Intelligent Computing, Communication and Devices. Advances in Intelligent Systems and Computing, vol 308. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2012-1_12
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DOI: https://doi.org/10.1007/978-81-322-2012-1_12
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