| Summary: | A parameter-free optimization technique is applied in Quasi-Newton’s method for solving unconstrained multiobjective optimization problems. The components of the Hessian matrix are constructed using <i>q</i>-derivative, which is positive definite at every iteration. The step-length is computed by an Armijo-like rule which is responsible to escape the point from local minimum to global minimum at every iteration due to <i>q</i>-derivative. Further, the rate of convergence is proved as a superlinear in a local neighborhood of a minimum point based on <i>q</i>-derivative. Finally, the numerical experiments show better performance.
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