Multi-strategy hybrid whale optimization algorithms for complex constrained optimization problems

A multi-strategy hybrid whale optimization algorithm(MSHWOA)for complex constrained optimization problems is proposed to overcome the drawbacks of easily trapping into local optimum,slow convergence speed and low optimization precision.Firstly,the population is initialized by introducing the theory of good point set,which increases the randomness and diversity of the population and lays the foundation for the global optimization of the algorithm.Then,a novel linearly update equation of convergence factor is designed to coordinate the abilities of exploration and exploitation.At the same time,the global exploration and local exploitation capabilities are improved through the siege mechanism of Harris Hawks optimization algorithm.Finally,the simulation experiments are conducted on the 6 benchmark functions and Wilcoxon rank sum test to evaluate the optimization performance of the improved algorithm.The experimental results show that the proposed algorithm has more significant improvement in optimization accuracy,convergence speed and robustness than the comparison algorithm.

Wind-induced response analysis of conical membrane structures

Conical membrane structures are a typical form of tensile membrane structures. In the past, most studies focused on the static performance, but few on dynamic performance. In this paper, systematic parameter analysis of wind-induced response of conical membrane structures has been performed with nonlinear random simulation method in a time domain, by considering some parameters, such as span, rise-span ratio, prestress of membrane, and characteristic of the approaching wind flow. Moreover, formulas of the dynamic coefficient and nonlinear adjustment factor are advised, which can be conveniently used in wind-resistant design of conical membrane structures.

A Novel Evolutionary-Fuzzy Control Algorithm for Complex Systems

This paper presents an adaptive fuzzy control scheme based on modified genetic algorithm. In the control scheme, genetic algorithm is used to optimze the nonlinear quantization functions of the controller and some key parameters of the adaptive control algorithm. Simulation results show that this control scheme has satisfactory performance in MIMO systems, chaotic systems and delay systems.

Progressive collapse resisting capacity of reinforced concrete load bearing wall structures

Reinforced concrete(RC) load bearing wall is widely used in high-rise and mid-rise buildings. Due to the number of walls in plan and reduction in lateral force portion, this system is not only stronger against earthquakes, but also more economical. The effect of progressive collapse caused by removal of load bearing elements, in various positions in plan and stories of the RC load bearing wall system was evaluated by nonlinear dynamic and static analyses. For this purpose, three-dimensional model of 10-story structure was selected. The analysis results indicated stability, strength and stiffness of the RC load-bearing wall system against progressive collapse. It was observed that the most critical condition for removal of load bearing walls was the instantaneous removal of the surrounding walls located at the corners of the building where the sections of the load bearing elements were changed. In this case, the maximum vertical displacement was limited to 6.3 mm and the structure failed after applying the load of 10 times the axial load bored by removed elements. Comparison between the results of the nonlinear dynamic and static analyses demonstrated that the "load factor" parameter was a reasonable criterion to evaluate the progressive collapse potential of the structure.

A CLASS OF FACTORIZED QUASI-NEWTON METHODS FOR NONLINEAR LEAST SQUARES PROBLEMS

This paper gives a class of descent methods for nonlinear least squares solution. A class of updating formulae is obtained by using generalized inverse matrices. These formulae generate an approximation to the second part of the Hessian matrix of the objective function, and are updated in such a way that the resulting approximation to the whole Hessian matrix is the convex class of Broyden-like up-dating formulae. It is proved that the proposed updating formulae are invariant under linear transformation and that the class of factorized quasi-Newton methods are locally and superlinearly convergent. Numerical results are presented and show that the proposed methods are promising.

Barut–Girardello Coherent States for Nonlinear Oscillator with Position-Dependent Mass

Using ladder operators for the non-linear oscillator with position-dependent effective mass, realization of the dynamic group SU(1,1) is presented. Keeping in view the algebraic structure of the non-linear oscillator, coherent states are constructed using Barut–Girardello formalism and their basic properties are discussed. Furthermore, the statistical properties of these states are investigated by means of Mandel parameter and second order correlation function. Moreover,it is shown that in the harmonic limit, all the results obtained for the non-linear oscillator with spatially varying mass reduce to corresponding results of the linear oscillator with constant mass.