The multi-starting descentmethod is a promising approach to unimodal multiobjective function optimization problems because of its precision of obtained solutions. descentmethods can be classified into two categories...
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ISBN:
(纸本)9781424481262
The multi-starting descentmethod is a promising approach to unimodal multiobjective function optimization problems because of its precision of obtained solutions. descentmethods can be classified into two categories;the multiobjective descentmethod directly using the Jacobian matrix of objective functions and the scalarizeddescentmethod using the gradient of a scalarized objective function. In the multiobjective descentmethod and the scalarizeddescentmethod, a convergent point depends on an initial solution and a weight vector, respectively. However, it is difficult to choose appropriate initial solutions or weight vectors for obtaining widely and evenly distributed solutions. In order to remedy the problems of the conventional methods, we propose a multi-starting scalarizeddescentmethod named AWA that employs the Chebyshev norm method as a scalarization method and an adaptive scheme of weight vectors for the scalarization method. We show the effectiveness of the proposed method through some experiments.
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