• 대한수학회논문집
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• 제25권2호
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• pp.313-325
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• 2010

General models for the relaxed proximal point algorithm using the notion of relative maximal accretiveness (RMA) are developed, and then the convergence analysis for these models in the context of solving a general class of nonlinear inclusion problems differs significantly than that of Rockafellar (1976), where the local Lipschitz continuity at zero is adopted instead. Moreover, our approach not only generalizes convergence results to real Banach space settings, but also provides a suitable alternative to other problems arising from other related fields.

• 충청수학회지
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• 제21권2호
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• pp.147-155
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• 2008

In this paper, we consider proximal point algorithms based on ($A,{\eta}$)-monotone mappings in the framework of Hilbert spaces. Since ($A,{\eta}$)-monotone mappings generalize A-monotone mappings, H-monotone mappings and many other mappings, our results improve and extend the recent ones announced by [R.U. Verma, Rockafellars celebrated theorem based on A-maximal monotonicity design, Appl. Math. Lett. 21 (2008), 355-360] and [ R.T. Rockafellar, Monotone operators and the proximal point algorithm, SIAM J. Control Optim. 14 (1976) 877-898] and some others.

• East Asian mathematical journal
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• 제26권5호
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• pp.703-714
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• 2010

A new class of nonlinear set-valued mixed variational inclusions involving (A, ${\eta}$)-accretive mappings in Banach spaces is introduced and studied, which includes many kind of variational inclusion (inequality) and complementarity problems as special cases. By using the resolvent operator associated with (A, ${\eta}$)-accretive operator due to Lan-Cho-Verma, the existence of solution for this kind of variational inclusion is proved, and a new hybrid proximal point algorithm is established and suggested, the convergence and stability theorems of iterative sequences generated by new iterative algorithms are also given in q-uniformly smooth Banach spaces.

• Nonlinear Functional Analysis and Applications
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• 제28권1호
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• pp.175-203
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• 2023

In this paper, we study an iterative algorithm that is based on inertial proximal and contraction methods embellished with relaxation technique, for finding common solution of monotone variational inclusion, and fixed point problems of pseudocontractive mapping in real Hilbert spaces. We establish a strong convergence result of the proposed iterative method based on prediction stepsize conditions, and under some standard assumptions on the algorithm parameters. Finally, some special cases of general problem are given as applications. Our results improve and generalized some well-known and related results in literature.

• 한국시뮬레이션학회논문지
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• 제27권4호
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• pp.1-8
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• 2018

인공지능을 이용하여 목표 지점까지 제어하는 가장 대표적인 방법은 강화학습이다. 하지만 그동안 강화학습을 처리하기 위해서는 구현하기 어렵고 복잡한 연산을 처리해야만 했다. 본 논문에서는 이를 개선한 Proximal Policy Optimization (PPO) 알고리즘을 이용하여 가상환경에서 목표지점에 도달하기 위한 계획된 비행궤적을 찾는 방법을 시뮬레이션 하였다. 또한 외부 환경요소가 비행궤적 학습에 미치는 영항을 알아보기 위하여 궤적의 변화, 보상 값의 영향 및 외부 바람등과 같은 변수를 추가하고 궤적 학습 성능 및 학습 속도에 미치는 영향을 비교 분석을 수행한다. 본 결과를 통하여 에이전트가 다양한 외부환경의 변화에도 계획된 궤적을 찾을 수 있다는 것을 시뮬레이션 결과에 따라 알 수 있었으며, 이는 실제 비행체에 적용할 수 있을 것이다.

• Kyungpook Mathematical Journal
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• 제59권1호
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• pp.101-123
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• 2019

In this paper, we consider a system of nonlinear variational type inclusions involving ($H,{\varphi},{\eta}$)-monotone operators in real Banach spaces. Further, we define a proximal operator associated with an ($H,{\varphi},{\eta}$)-monotone operator and show that it is single valued and Lipschitz continuous. Using proximal point operator techniques, we prove the existence and uniqueness of a solution and suggest an iterative algorithm for the system of nonlinear variational type inclusions. Furthermore, we discuss the convergence of the iterative sequences generated by the algorithms.

• Nonlinear Functional Analysis and Applications
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• 제27권1호
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• pp.1-22
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• 2022

The purpose of this research is to formulate a new proximal-type algorithm to solve the equilibrium problem in a real Hilbert space. A new algorithm is analogous to the famous two-step extragradient algorithm that was used to solve variational inequalities in the Hilbert spaces previously. The proposed iterative scheme uses a new step size rule based on local bifunction details instead of Lipschitz constants or any line search scheme. The strong convergence theorem for the proposed algorithm is well-proven by letting mild assumptions about the bifunction. Applications of these results are presented to solve the fixed point problems and the variational inequality problems. Finally, we discuss two test problems and computational performance is explicating to show the efficiency and effectiveness of the proposed algorithm.

• 대한수학회보
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• 제54권4호
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• pp.1347-1359
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• 2017

The purpose of this paper is to give some new iterative methods for finding a common zero of a finite family of monotone operators in Hilbert spaces. We also give the applications of the obtained result for the convex feasibility problem and constrained convex optimization problem in Hilbert spaces.

• East Asian mathematical journal
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• 제24권2호
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• pp.177-186
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• 2008

In this paper, we introduce and study a new class of system of parametric general quasivariational-like inequalities. Using $\eta$-subdifferential and $\eta$-proximal mappings of proper functionals in Hilbert spaces, we prove the equivalence between the system of parametric general quasivariational-like inequalities and a xed point problem and construct two iterative algorithms. A few existence and uniqueness results as well as the sensitivity analysis of solutions are also established for the system of parametric general quasivariational-like inequalities, and some convergence results of iterative sequence generated by the algorithms are proved. Our results extend a few known results in the literature.

• 대한전기학회논문지:전력기술부문A
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• 제48권11호
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• pp.1424-1428
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• 1999

This paper presents a mathematical decomposition coordination method to implementing the distributed optimal power flow (OPF), wherein a regional decomposition technique is adopted to parallelize the OPT. The proposed approach is based on the Alternating Direction Method (ADM), a variant of the conventional Augmented Lagrangian approach, and makes it possible the independent regional AC-OPF for each control area while the global optimum for the entire system is assured. This paper is an extension of our previous work based on the auxiliary problem principle (APP). The proposed approach in this paper is a completely new one, however, in that ADM is based on the Proximal Point Algorithm which has long been recognized as one of the attractive methods for convex programming and min-max-convex-concave programming. The proposed method was demonstrated with IEEE 50-Bus system.