Fuzzy Structural Analysis Using Improved Jaya-based Optimization Approach

A new approach to performing the α-level optimization in the fuzzy analysis of structural systems is developed in this study. The method uses a simple global optimizer, the Jaya algorithm, together with an innovative dimension reduction technique. The dimension reduction technique aims to transform the original large α-level optimization problem into a low-dimension one by making use of the monotonic behavior of the system output with respect to the input variables. Then, the Jaya algorithm is applied to solve the reduced max/min α-level optimization problems to determine the bounds of the fuzzy output. Two numerical examples, including a 2D truss and a 3D truss, with a relatively large number of fuzzy input variables are analyzed and the fuzzy displacements under static loads are predicted. It is demonstrated that the proposed approach can save a significant computational amount and also estimate the fuzzy displacement with high accuracy

Inexact proximal methods for weakly convex functions

This paper proposes and develops inexact proximal methods for finding stationary points of the sum of a smooth function and a nonsmooth weakly convex one, where an error is present in the calculation of the proximal mapping of the nonsmooth term. A general framework for finding zeros of a continuous mapping is derived from our previous paper on this subject to establish convergence properties of the inexact proximal point method when the smooth term is vanished and of the inexact proximal gradient method when the smooth term satisfies a descent condition. The inexact proximal point method achieves global convergence with constructive convergence rates when the Moreau envelope of the objective function satisfies the Kurdyka-Lojasiewicz (KL) property. Meanwhile, when the smooth term is twice continuously differentiable with a Lipschitz continuous gradient and a differentiable approximation of the objective function satisfies the KL property, the inexact proximal gradient method achieves the global convergence of iterates with constructive convergence rates.Comment: 26 pages, 3 table

ĐẶC ĐIỂM ĐỊA HÌNH ĐÁY VÀ TRẦM TÍCH TẦNG MẶT VÙNG BIỂN QUẦN ĐẢO THỔ CHU

Tho Chu archipelago was formed by sedimentary rocks (176 metres in height) with horizontal position. The islands are limited by the abraded slopes and landslide disruption. The shoreline morphology is cliffs, abrasion and boulders with good size, low abrasion, and little change. Vegetation of island is still in the primary condition. The average depth of Tho Chu archipelago is about 20 - 30 m with canyons of -96 m and several underwater hills which are covered by coral reefs. The characteristics of seabed sediment are mostly kinds of coarse - grained sediments such as gravelly sand (gS), slightly gravelly muddy sand ((g)mS), muddy sand (mS), mud (M).Quần đảo Thổ Chu được cấu tạo bởi các đá trầm tích (cao 176 m), có thế nằm ngang. Xung quanh đảo được giới hạn các sườn dốc mài mòn và đỗ vỡ sụp lở. Hình thái đường bờ là các vách dốc, mài mòn và các tảng lăn với kích thước khá lớn, bị mài mòn yếu, ít bị thay đổi, thảm thực vật trên đảo còn nguyên sinh. Độ sâu trung bình quần đảo Thổ Chu khoảng 20 - 30 m, có rãnh sâu có độ sâu -96 m và có rất nhiều đồi ngầm phần lớn được phủ san hô. Đặc điểm trầm tích tầng mặt được phủ bởi các kiểu trầm tích hạt thô: Cát chứa graven, cát chứa bùn sét (và graven), cát chứa bùn sét, bùn sét

A New Inexact Gradient Descent Method with Applications to Nonsmooth Convex Optimization

The paper proposes and develops a novel inexact gradient method (IGD) for minimizing C1-smooth functions with Lipschitzian gradients, i.e., for problems of C1,1 optimization. We show that the sequence of gradients generated by IGD converges to zero. The convergence of iterates to stationary points is guaranteed under the Kurdyka- Lojasiewicz (KL) property of the objective function with convergence rates depending on the KL exponent. The newly developed IGD is applied to designing two novel gradient-based methods of nonsmooth convex optimization such as the inexact proximal point methods (GIPPM) and the inexact augmented Lagrangian method (GIALM) for convex programs with linear equality constraints. These two methods inherit global convergence properties from IGD and are confirmed by numerical experiments to have practical advantages over some well-known algorithms of nonsmooth convex optimization.Comment: 23 pages, 8 figure

General Derivative-Free Optimization Methods under Global and Local Lipschitz Continuity of Gradients

This paper addresses the study of derivative-free smooth optimization problems, where the gradient information on the objective function is unavailable. Two novel general derivative-free methods are proposed and developed for minimizing such functions with either global or local Lipschitz continuous gradients. The newly developed methods use gradient approximations based on finite differences, where finite difference intervals are automatically adapted to the magnitude of the exact gradients without knowing them exactly. The suggested algorithms achieve fundamental convergence results, including stationarity of accumulation points in general settings as well as global convergence with constructive convergence rates when the Kurdyka-\L ojasiewicz property is imposed. The local convergence of the proposed algorithms to nonisolated local minimizers, along with their local convergence rates, is also analyzed under this property. Numerical experiences involving various convex, nonconvex, noiseless, and noisy functions demonstrate that the new methods exhibit essential advantages over other state-of-the-art methods in derivative-free optimization.Comment: 30 pages, 49 figure

DEVELOPMENT AND EVALUATION OF ORAL SUSTAINED-RELEASE RANITIDINE DELIVERY SYSTEM BASED ON BACTERIAL NANOCELLULOSE MATERIAL PRODUCED BY KOMAGATAEIBACTER XYLINUS

Objective: The short biological half-life (2-3 h) and low bioavailability (50 %) of ranitidine (RAN) following oral administration favor the development of a controlled release system. This study was aimed to develop and in vitro evaluate oral sustained-release RAN delivery system based on the bacterial nanocellulose material (BNM) produced by Komagataeibacter xylinus (K. xylinus) from selected culture media. Methods: BNMs are biosynthesized by K. xylinus in the standard medium (SM) and coconut water (CW). RAN was loaded in BNMs by the absorption method. The structural and physicochemical properties of BNMs and BNMs-RAN were evaluated via swelling behavior, FTIR, and FESEM techniques. Moreover, the effect of BNMs on RAN release profile and release kinetics was analyzed and evaluated. Results: The amount of loaded RAN or entrapment efficacy for BNM-CW is higher than for BNM-SM. The BNM-SM-RAN and BNM-CW-RAN exhibited a decreased initial burst release system followed by a prolonged RAN release up to 24 h in relation to the commercial tablets containing RAN. The RAN release from these formulations was found higher in the SGF medium than that of in SIF medium. RAN released from these formulations was found to follow the Korsmeyer-Peppas model and diffusion sustained drug release mechanism. The sustained release of RAN from BNM-SM-RAN was slower than for RAN from BNM-CW-RAN, but the mechanism of sustained RAN release was the same. Conclusion: Oral sustained-release RAN delivery system based on BNMs was successfully prepared and evaluated for various in vitro parameters. The biopolymers like BNM-SM and BNM-CW could be utilized to develop oral sustained RAN release dosage form