Please use this identifier to cite or link to this item:
|Title:||Pareto front approximation with adaptive weighted sum method in multiobjective simulation optimization|
|Source:||Ryu, J.-H.,Kim, S.,Wan, H. (2009). Pareto front approximation with adaptive weighted sum method in multiobjective simulation optimization. Proceedings - Winter Simulation Conference : 623-633. ScholarBank@NUS Repository. https://doi.org/10.1109/WSC.2009.5429562|
|Abstract:||This work proposes a new method for approximating the Pareto front of a multi-objective simulation optimization problem (MOP) where the explicit forms of the objective functions are not available. The method iteratively approximates each objective function using a metamodeling scheme and employs a weighted sum method to convert the MOP into a set of single objective optimization problems. The weight on each single objective function is adaptively determined by accessing newly introduced points at the current iteration and the non-dominated points so far. A trust region algorithm is applied to the single objective problems to search for the points on the Pareto front. The numerical results show that the proposed algorithm efficiently generates evenly distributed points for various types of Pareto fronts. ©2009 IEEE.|
|Source Title:||Proceedings - Winter Simulation Conference|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 5, 2017
checked on Dec 9, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.