On q-steepest descent method for unconstrained multiobjective optimization problems

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Last updated 22 dezembro 2024
On q-steepest descent method for unconstrained multiobjective optimization  problems
The <i>q</i>-gradient is the generalization of the gradient based on the <i>q</i>-derivative. The <i>q</i>-version of the steepest descent method for unconstrained multiobjective optimization problems is constructed and recovered to the classical one as <i>q</i> equals 1. In this method, the search process moves step by step from global at the beginning to particularly neighborhood at last. This method does not depend upon a starting point. The proposed algorithm for finding critical points is verified in the numerical examples.
On q-steepest descent method for unconstrained multiobjective optimization  problems
On q-steepest descent method for unconstrained multiobjective optimization problems
On q-steepest descent method for unconstrained multiobjective optimization  problems
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On q-steepest descent method for unconstrained multiobjective optimization  problems
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On q-steepest descent method for unconstrained multiobjective optimization  problems
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On q-steepest descent method for unconstrained multiobjective optimization  problems
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On q-steepest descent method for unconstrained multiobjective optimization  problems
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On q-steepest descent method for unconstrained multiobjective optimization  problems
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On q-steepest descent method for unconstrained multiobjective optimization  problems
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On q-steepest descent method for unconstrained multiobjective optimization  problems
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On q-steepest descent method for unconstrained multiobjective optimization  problems
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