scholarly journals Geodesic $ \mathcal{E} $-prequasi-invex function and its applications to non-linear programming problems

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Akhlad Iqbal ◽  
Praveen Kumar

<p style='text-indent:20px;'>In this article, we define a new class of functions on Riemannian manifolds, called geodesic <inline-formula><tex-math id="M2">\begin{document}$ \mathcal{E} $\end{document}</tex-math></inline-formula>-prequasi-invex functions. By a suitable example it has been shown that it is more generalized class of convex functions. Some of its characteristics are studied on a nonlinear programming problem. We also define a new class of sets, named geodesic slack invex set. Furthermore, a sufficient optimality condition is obtained for a nonlinear programming problem defined on a geodesic local <inline-formula><tex-math id="M3">\begin{document}$ \mathcal{E} $\end{document}</tex-math></inline-formula>-invex set.</p>

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Mohamed Jleli ◽  
Erdal Karapınar ◽  
Bessem Samet

LetAandBbe nonempty subsets of a metric space with the distance function d, andT:A→Bis a given non-self-mapping. The purpose of this paper is to solve the nonlinear programming problem that consists in minimizing the real-valued functionx↦d(x,Tx), whereTbelongs to a new class of contractive mappings. We provide also an iterative algorithm to find a solution of such optimization problems.


Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1551
Author(s):  
Bothina El-Sobky ◽  
Yousria Abo-Elnaga ◽  
Abd Allah A. Mousa ◽  
Mohamed A. El-Shorbagy

In this paper, a penalty method is used together with a barrier method to transform a constrained nonlinear programming problem into an unconstrained nonlinear programming problem. In the proposed approach, Newton’s method is applied to the barrier Karush–Kuhn–Tucker conditions. To ensure global convergence from any starting point, a trust-region globalization strategy is used. A global convergence theory of the penalty–barrier trust-region (PBTR) algorithm is studied under four standard assumptions. The PBTR has new features; it is simpler, has rapid convergerce, and is easy to implement. Numerical simulation was performed on some benchmark problems. The proposed algorithm was implemented to find the optimal design of a canal section for minimum water loss for a triangle cross-section application. The results are promising when compared with well-known algorithms.


Author(s):  
Tarunraj Singh

The focus of this paper is on the design of robust input shapers where the maximum value of the cost function over the domain of uncertainty is minimized. This nonlinear programming problem is reformulated as a linear programming problem by approximating a n-dimensional hypersphere with multiple hyperplanes (as in a geodesic dome). A recursive technique to approximate a hypersphere to any level of accuracy is developed using barycentric coordinates. The proposed technique is illustrated on the spring-mass-dashpot and the benchmark floating oscillator problem undergoing a rest-to-rest maneuver. It is shown that the results of the linear programming problem are nearly identical to that of the nonlinear programming problem.


Robotica ◽  
1994 ◽  
Vol 12 (5) ◽  
pp. 401-410 ◽  
Author(s):  
Chia-Ju Wu

SUMMARYIn this paper, a numerical approach is proposed to solve the time-optimal path-planning (TOPP) problem of kinematically redundant manipulators between two end-points. The first step is to transform the TOPP problem into a nonlinear programming problem by an iterative procedure. Then an approach to find the initial feasible solutions of the problem is proposed. Since initial feasible solutions can be found easily, the optimization process of the nonlinear programming problem can be started from different points to find the global minimum. A planar three-link robotic manipulator is used to illustrate the validity of the proposed approach.


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