Hybrid Artificial Bee Colony Algorithm and Particle Swarm Search for Global Optimization

Artificial bee colony (ABC) algorithm is one of the most recent swarm intelligence based algorithms, which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To overcome this problem, we propose a novel artificial bee colony algorithm based on particle swarm search mechanism. In this algorithm, for improving the convergence speed, the initial population is generated by using good point set theory rather than random selection firstly. Secondly, in order to enhance the exploitation ability, the employed bee, onlookers, and scouts utilize the mechanism of PSO to search new candidate solutions. Finally, for further improving the searching ability, the chaotic search operator is adopted in the best solution of the current iteration. Our algorithm is tested on some well-known benchmark functions and compared with other algorithms. Results show that our algorithm has good performance

Global Minimization for Generalized Polynomial Fractional Program

This paper is concerned with an efficient global optimization algorithm for solving a kind of fractional program problem (P), whose objective and constraints functions are all defined as the sum of ratios generalized polynomial functions. The proposed algorithm is a combination of the branch-and-bound search and two reduction operations, based on an equivalent monotonic optimization problem of (P). The proposed reduction operations specially offer a possibility to cut away a large part of the currently investigated region in which the global optimal solution of (P) does not exist, which can be seen as an accelerating device for the solution algorithm of (P). Furthermore, numerical results show that the computational efficiency is improved by using these operations in the number of iterations and the overall execution time of the algorithm, compared with other methods. Additionally, the convergence of the algorithm is presented, and the computational issues that arise in implementing the algorithm are discussed. Preliminary indications are that the algorithm can be expected to provide a practical approach for solving problem (P) provided that the number of variables is not too large

A Global Optimization Approach for Solving Generalized Nonlinear Multiplicative Programming Problem

This paper presents a global optimization algorithm for solving globally the generalized nonlinear multiplicative programming (MP) with a nonconvex constraint set. The algorithm uses a branch and bound scheme based on an equivalently reverse convex programming problem. As a result, in the computation procedure the main work is solving a series of linear programs that do not grow in size from iterations to iterations. Further several key strategies are proposed to enhance solution production, and some of them can be used to solve a general reverse convex programming problem. Numerical results show that the computational efficiency is improved obviously by using these strategies

A Global Optimization Algorithm for Signomial Geometric Programming Problem

This paper presents a global optimization algorithm for solving the signomial geometric programming (SGP) problem. In the algorithm, by the straight forward algebraic manipulation of terms and by utilizing a transformation of variables, the initial nonconvex programming problem (SGP) is first converted into an equivalent monotonic optimization problem and then is reduced to a sequence of linear programming problems, based on the linearizing technique. To improve the computational efficiency of the algorithm, two range reduction operations are combined in the branch and bound procedure. The proposed algorithm is convergent to the global minimum of the (SGP) by means of the subsequent solutions of a series of relaxation linear programming problems. And finally, the numerical results are reported to vindicate the feasibility and effectiveness of the proposed method

合唱活动对中老年的健康促进

Objective: Assessment of chorus activity on elderly health promotion in the level of immunity, cardiopulmonary function and mental health. Methods: 3 groups of related data within 68 members in the chorus before training, training for 6 months and 12 months were counted and analyzed by computer analysis software. Compared with 50 cases of the same age group, that was collected at the same period, about data at 3 stages. Results: The average data of three phases of chorus is: immune level (CD4): 662.38, 761.22, 764.15, left ventricular ejection fraction (LVEF): 61.11, 61.13, 62.66, short axial shortening rate (FS): 32.61, 32.88, 33.65, lung function tidal volume (TV):1.06, 1.18, 1.16, forced vital capacity (FVC): 2.76, 2.85, 2.95, 1s forced expiratory volume (FEV1): 2.31, 2.42, 2.55, 1s rate (FEV1/FVC): 83.69, 84.91, 86.44, the chase volume (MVV is): 83.25, 81.11, 81.93, mental health score values 124.44, 125.67, 126.22, in addition to that, the TV, MVV and mental health score (SF - 36) did not change outside, other indicators, including the CD4, LVEF, FS, FVC, FEV and FEV1/FVC all have different degrees of ascension. Among them, the CD4 in training after 6 months improved obviously, little change after 12 months. Cardiac function index: EF and FS were improved after training 12 months. Lung function, FEV1, FVC, FEV1/FVC are ascending after training for 6 months and for 12 months. The average data of three phases)of the other group is: immune level (CD4) : 660.24, 661.85, 661.32, left ventricular ejection fraction (LVEF): 61.33, 61.28, 61.31, short axial shortening rate (FS): 32.55, 32.38, 32.46, lung function tidal volume (TV): 1.16, 1.17, 1.16，forced vital capacity (FVC): 2.74, 2.76, 2.76, 1s forced expiratory volume (FEV1): 2.30, 2.31, 2.30,1s rate (FEV1/FVC): 83.94, 83.69, 83.33, the chase volume (MVV is): 83.35, 82.49, 83.06, mental health score values 125.31, 124.86, 124.93. No changes were found in all measurement data of all 3 stages in the other group. Conclusions: The scientific, reasonable and continued chorus training has different degrees of help for raising the level of immune, improving cardiopulmonary function and raising the level of overall health to elderly.目的  评估合唱活动对中老年人群在机体免疫水平、心肺功能及心理健康等方面的促进作用。方法  运用计算机分析软件，对某中老年合唱团68名成员在合唱训练前（第一阶段）、训练6个月（第二阶段）、训练12个月后（第三阶段）所采集的3组数据进行回顾性同比统计分析，并与同期50例同年龄段人群采集的3阶段数据进行比对。结果  合唱团三阶段3组数据各自平均值的变化如下：机体免疫水平（CD4）：662.38、761.22、764.15；心功能左室射血分数（LVEF）值：61.11、61.13、62.66；短轴缩短率（FS）值：32.61、32.88、33.65；肺功能潮气量（TV）值：1.16、1.18、1.16；用力肺活量（FVC）值：2.76、2.85、2.95，第1秒用力呼气容量（FEV1）值：2.31、2.42、2.55，1s率（FEV1/FVC）值：83.69、84.91、86.44；最大通气量（MVV）值：83.25、81.11、81.93；心理健康评分值124.44、125.67、126.22。该组数据除了TV、MVV和健康调查简表（SF-36）没有变化外，其他指标，包括CD4、LVEF、FS、FVC、FEV1和FEV1/FVC均有不同程度的提升。其中，CD4在训练6月后提升明显，第三阶段变化不大。心功能指标：LVEF和FS则在训练12个月后才有提高。肺功能FVC、FEV1和FEV1/FVC则在训练6个月、12个月两个阶段均有提升。非合唱组3阶段3组数据各自平均值的变化如下：CD4：660.24、661.85、661.32；LVEF：61.33、61.28、61.31；FS：32.55、32.38、32.46；TV：1.16、1.17、1.16；FVC：2.74、2.76、2.76；FEV1：2.30、2.31、2.30；FEV1/FVC：83.94、83.69、83.33；MVV：83.35、82.49、83.06；心理健康评分值125.31、124.86、124.93。该组所有测数据3阶段比对均无明显变化。结论  科学、合理、持续的合唱训练，对中老年免疫水平的提高、心肺功能的改善和整体健康水平的提高有着不同程度的帮助