ANew Theoretical Framework forAnalyzing Stochastic Global Optimization Algorithms

In this paper, we develop a new theoretical framework by means of the absorbing Markov process theory for analyzing some stochastic global optimization algorithms. Applying the framework to the pure random search, we prove that the pure random search converges to the global minimum in probability and its time has geometry distribution. We also analyze the pure adaptive search by this framework and turn out that the pure adaptive search converges to the global minimum in probability and its time has Poisson distribution.

Multi-swingby optimization of mission to Saturn using global optimization algorithms

Based on the trajectory design of a mission to Saturn, this paper discusses four different trajectories in various swingby cases. We assume a single impulse to be applied in each case when the spacecraft approaches a celestial body. Some optimal trajectories ofEJS, EMS, EVEJS and EVVEJS flying sequences are obtained using five global optimization algorithms： DE, PSO, DP, the hybrid algorithm PSODE and another hybrid algorithm, DPDE. DE is proved to be supe- rior to other non-hybrid algorithms in the trajectory optimi- zation problem. The hybrid algorithm of PSO and DE can improve the optimization performance of DE, which is vali- dated by the mission to Saturn with given swingby sequences. Finally, the optimization results of four different swingby sequences are compared with those of the ACT of ESA.

A New Stochastic Algorithm of Global Optimization ——Region's Walk and Contraction

This paper presents a new stochastic algorithm for box constrained global optimization problem. Bacause the level set of objective function is always not known, the authors designed a region containing the current minimum point to replace it, and in order to fit the level set well, this region would be walking and contracting in the running process. Thus, the new algorithm is named as region's walk and contraction(RWC). Some numerical experiments for the RWC were conducted, which indicate good property of the algorithm.

Novel Global Optimization Algorithm with a Space-Filling Curve and Integral Function

In this study,we consider the global optimization problem in a hypercube.We use a class of series to construct a curve in a hypercube,which can fill the hypercube,and we present an integral function on the curve.Based on the integral function,we propose an algorithm for solving the global optimization problem.Then,we perform a convergence analysis and numerical experiments to demonstrate the effectiveness of the proposed algorithm.

Multiobjective Optimization of Hull Form Based on Global Optimization Algorithm

Rankine source method,optimization technology,parametric modeling technology,and improved multiobjective optimization algorithm were combined to investigate the multiobjective optimization design of hull form.A multiobjective and multilevel optimization design framework was constructed for the comprehensive navigation performance of ships.CAESES software was utilized as the optimization platform,and nondominated sorting genetic algorithm II(NSGA-II)was used to conduct multiobjective optimization research on the resistance and sea-keeping performance of the ITTC Ship A-2 fishing vessel.Optimization objectives of this study are heave/pitch response amplitude and wave-making resistance.Taking the displacement and the length between perpendiculars as constraints,we optimized the profile of the hull.Analytic hierarchy process(AHP)and technique for order preference by similarity to ideal solution(TOPSIS)were used to sort and select Pareto solutions and determine weight coefficient of each navigation performance objective in the general objective.Finally,the hydrodynamic performance before and after the parametric deformation of the hull was compared.The results show that both the wave-making resistance and heave/pitch amplitude of the optimized hull form are reduced,and the satisfactory optimal hull form is obtained.The results of this study have a certain reference value for the initial stage of multiobjective optimization design of hull form.

Improvement of Pure Random Search in Global Optimization

In this paper, the improvement of pure random search is studied. By taking some information of the function to be minimized into consideration, the authors propose two stochastic global optimization algorithms. Some numerical experiments for the new stochastic global optimization algorithms are presented for a class of test problems.

Mechanical Characteristics Analysis of 3D-printing Novel Chiral Honeycomb Array Structures Based on Functional Principle and Constitutive Relationship

Four novel chiral honeycomb structures inspired by the biological arrangement shape are designed.The functional principle is raised to solve the large deformation of bio-inspired structures and the structural constitutive model is proposed to explain the quasi-static mechanical properties of chiral honeycomb array structures and honeycomb structures.Simulation and experiment results verify the accuracy of theoretical analysis results and the errors are all within 15%.In structural mechanical properties,Equidimensional Chiral Honeycomb Array Structure(ECHS)has excellent mechanical properties.Among ECHS,Small-sized Column Chiral Honeycomb Array Structure(SCHCS)has the best properties.The bearing capacity,specific energy absorption,and specific strength of SCHCS are more than twice as much as the others in this paper.The chiral honeycomb array structure has the best mechanical properties at a certain size.In the structural design,the optimal size model should be obtained first in combination with the optimization algorithm for the protection design.