保险公司资产的最优投资

针对给定初始准备金前提下,如何对保险公司的资产进行合理的投资.利用随机控制中HJB方程的相关理论,将总收益满足的随机微分方程转化为二阶非线性常微分方程.求解得到目标值函数的最优值表达式,最终确定出能够给保险公司投资债券行业带来最大收益的投资策略.研究结果表明:保险公司的最优投资策略不仅取决于债券市场的风险大小,还取决于保费收益率、索赔到达的强度以及债券风险收益率等.

Discontinuous flying particle swarm optimization algorithm and its application to slope stability analysis

A new version of particle swarm optimization(PSO) called discontinuous flying particle swarm optimization(DFPSO) was proposed,where not all of the particles refreshed their positions and velocities during each iteration step and the probability of each particle in refreshing its position and velocity was dependent on its objective function value.The effect of population size on the results was investigated.The results obtained by DFPSO have an average difference of 6% compared with those by PSO,whereas DFPSO consumes much less evaluations of objective function than PSO does.

A new algorithm for estimating gillnet selectivity

The estimation of gear selectivity is a critical issue in fishery stock assessment and management.Several methods have been developed for estimating gillnet selectivity,but they all have their limitations,such as inappropriate objective function in data fitting,lack of unique estimates due to the difficulty in finding global minima in minimization,biased estimates due to outliers,and estimations of selectivity being influenced by the predetermined selectivity functions.In this study,we develop a new algorithm that can overcome the above-mentioned problems in estimating the gillnet selectivity.The proposed algorithms include minimizing the sum of squared vertical distances between two adjacent points and minimizing the weighted sum of squared vertical distances between two adjacent points in the presence of outliers.According to the estimated gillnet selectivity curve,the selectivity function can also be determined.This study suggests that the proposed algorithm is not sensitive to outliers in selectivity data and improves on the previous methods in estimating gillnet selectivity and relative population density of fish when a gillnet is used as a sampling tool.We suggest the proposed approach be used in estimating gillnet selectivity.

Multi-Objective Genetic Algorithm to Design Manufacturing Process Line Including Feasible and Infeasible Solutions in Neighborhood

This paper treats multi-objective problem for manufacturing process design. A purpose of the process design is to decide combinations of work elements assigned to different work centers. Multiple work elements are ordinarily assigned to each center. Here, infeasible solutions are easily generated by precedence relationship of work elements in process design. The number of infeasible solutions generated is ordinarily larger than that of feasible solutions generated in the process. Therefore, feasible and infeasible solutions are located in any neighborhood in solution space. It is difficult to seek high quality Pareto solutions in this problem by using conventional multi-objective evolutional algorithms. We consider that the problem includes difficulty to seek high quality solutions by the following characteristics： （1） Since infeasible solutions are resemble to good feasible solutions, many infeasible solutions which have good values of objective functions are easily sought in the search process, （2） Infeasible solutions are useful to select new variable conditions generating good feasible solutions in search process. In this study, a multi-objective genetic algorithm including local search is proposed using these characteristics. Maximum value of average operation times and maximum value of dispersion of operation time in all work centers are used as objective functions to promote productivity. The optimal weighted coefficient is introduced to control the ratio of feasible solutions to all solutions selected in crossover and selection process in the algorithm. This paper shows the effectiveness of the proposed algorithm on simple model.

Optimal Design of Splitters Attached to Turbo Blower Impeller by RSM

This paper describes the optimization of the impeller having splitters for a turbo blower.Two design variables,chord of splitter and pitch of splitter,are introduced to enhance the blower performance.Blower pressure and ef-ficiency are selected as an object function,and the optimization of the blower impeller is performed by a response surface method (RSM).Three-dimensional Navier-Stokes equations are introduced to analyze the internal flow of the blower and to find the value of the object function for each case.Throughout the shape optimization of the splitters attached to the impeller in the turbo blower,pressure and efficiency at the design flow condition are suc-cessively increased by 5.9 percent and 17.9 percent respectively based on the reference blower.The higher blower efficiency obtained by optimization of impeller having splitters is mainly caused by reducing the number of im-peller blades and optimal design of splitters in the blade passage while pressure increase keeps almost the same with the reference blower.For the object function of pressure,pressure increase is obtained at the design and off-design conditions while efficiency keeps higher compared to the reference blower.The enhancement of blow-er performance is due to the reduction of reverse and circulation flows in the blade passage.

An approach for shape optimization of stratosphere airships based on multidisciplinary design optimization

Airship shape is crucial to the design of stratosphere airships. In this paper, multidisciplinary design optimization (MDO) technology is introduced into the design of airship shape. We devise a composite objective function, based on this technology, which takes account of various factors which influence airship performance, including aerodynamics, structures, energy and weight to determine the optimal airship shape. A shape generation algorithm is proposed and appropriate mathematical models are constructed. Simulation results show that the optimized shape gives an improvement in the value of the composite objective function compared with a reference shape.

Enhancement of Performance by Blade Optimization in Two-Stage Ring Blower

This paper describes the shape optimization of an impeller used for two-stage high pressure ring blower.Two shape variables,which are used to define an impeller shape,are introduced to increase the blower performance.The pressure of a blower is selected as an object function,and the blade optimization is performed by a response surface method.Three-dimensional Navier-Stokes equations are introduced to analyze the internal flow of the blower and to find the value of object function for the training data.Relatively good agreement between experimental measurements and numerical simulation is obtained in the present study.Throughout the shape optimization,it is found that a hub height is effective to increase pressure in the ring blower.The pressure rise for the optimal two-stage ring blower is successfully increased up to 1.86% compared with that of reference at the design flow rate.Local recirculation flow having low velocity is formed in both sides of the impeller outlet by different flow direction of the inlet and outlet of the impeller.Detailed flow field inside the ring blower is also analyzed and discussed.

A proximal alternating linearization method for minimizing the sum of two convex functions

In this paper, we develop a novel alternating linearization method for solving convex minimization whose objective function is the sum of two separable functions. The motivation of the paper is to extend the recent work Goldfarb et al.(2013) to cope with more generic convex minimization. For the proposed method,both the separable objective functions and the auxiliary penalty terms are linearized. Provided that the separable objective functions belong to C1,1(Rn), we prove the O(1/?) arithmetical complexity of the new method. Some preliminary numerical simulations involving image processing and compressive sensing are conducted.