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ENGTRANSACTIONS 2, 7 pages - Article ID: ENGT-2107132112371




An Improved Non-dominated Sorting Method in Genetic Algorithm for Bi-objective Problems


Authors

Mirpouya Mirmozaffari


Department of Industrial Engineering, Faculty of Engineering, Dalhousie University, Halifax, NS, Canada
ABSTRACT

This paper proposes a new non-dominated-sorting method for non-dominated sorting genetic algorithm (NSGA2). This method combines crowding distance and distance-based methods for non-dominated-sorting. The distance-based method identifies concavities on the Pareto Front curve and selects the solutions located at these points. Our goal in this method is to converge faster and find more optimal solutions in the Genetic Algorithm. The Numerical example shows that the results obtained from NSGA2 method with modified non-dominated sorting are better than regular NSGA2.


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