细菌觅食算法求解二次分配问题

为有效解决二次分配问题,提出了一种基于群体搜索的群智能优化算法—细菌觅食算法.算法模拟了细菌觅食全过程,并将细菌个体信息与探索细菌群体信息进行结合,采用了群体搜索策略进行局部寻优.该策略有效的避免了算法陷入局部最优,而算法中采用的自适应搜索步长,进一步提高了优化的收敛速度.实验结果表明,用细菌觅食算法解决二次分配问题,并将仿真结果与其他算法进行比较,表明了该算法的搜索质量优于其他算法.     

Essential-Oil-Mediated Interactions Between Oregano Plants and Helicidae Grazers

Aromatic plants dominate in Mediterranean-type ecosystems. They often produce remarkable quantities of essential oils containing high amounts of phenolic isoprenoids, such as thymol and carvacrol. The purpose of this work was to examine the interactions between commonly occurring aromatic plants in the Mediterranean environment and their snail grazers. The aromatic plants used were two Origanum vulgare subspecies, subsp. hirtum and subsp. vulgare. They differ in the content and the qualitative composition of their essential oil; subsp. hirtum contains a much larger amount and is rich in phenolic compounds. Their effect on the foraging behavior of three snail species, native in Greece, was studied; the snail species were Helix lucorum, H. aspersa, and Eobania vermiculata. The snails' responses to different food sources, raw or processed, with or without essential oils, were evaluated during the different stages of the foraging cycle. During the encounter stage, snails were more repelled than attracted when close to phenol-rich foods. During the acceptance stage, all snail species tended to reject food types that contained high concentrations of subsp. hirtum essential oil. At the feeding stage, subsp. hirtum essential oil caused reduction of daily consumption rates. Overall, the essential oil of O. vulgare subsp. vulgare did not produce any marked change in the snails' behavior. In contrast, that of O. vulgare subsp. hirtum had a repellent effect, particularly when present in naturally occurring high concentrations. Among the snail species, H. lucorum, which does not share the same biotope with O. vulgare subsp. hirtum, was the least tolerant to its essential oil.     

The Striped Mouse (Rhabdomys pumilio) From the Succulent Karoo, South Africa: A Territorial Group-Living Solitary Forager With Communal Breeding and Helpers at the Nest.

The authors studied the striped mouse (Rhabdomys pumilio) in the semiarid succulent karoo of South Africa. Mice forage alone, but they live in groups that share a common nest. Groups consist of 1 to 4 breeding females, 1 to 2 breeding males, and their offspring of both sexes, which remain in their natal group even after reaching adulthood, participating in territorial defense and nest building without showing signs of reproductive activity. Interactions are typically amicable and take place inside or in front of the nest. In contrast, encounters with mice from other groups are aggressive. Group living in the succulent karoo is possibly due to ecological constraints imposed by habitat saturation because of a year-round stable food supply as well as associated benefits of philopatry. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于细菌觅食优化算法的永磁同步电机位置伺服系统模糊控制策略

针对PID控制器参数固定而引起永磁同步电机(PMSM)位置伺服系统控制效果不佳问题,设计了基于细菌觅食优化算法的模糊控制器。该位置控制系统是以空间矢量控制为理论基础,由位置环、速度环、电流环构成的PMSM三闭环控制系统。在MATLAB/Simulink环境中将模糊控制器应用在系统位置环上。对比仿真结果发现,参数优化后的模糊控制器在系统位置环的作用更加优越,完全克服了传统PID控制器的缺点,能有效提高电机位置控制的快速性和准确性。     

Revolute manipulator workspace optimization using a modified bacteria foraging algorithm: A comparative study

Robotic manipulators with three-revolute (3R) motions to attain desired positional configurations are very common in industrial robots. The capability of these robots depends largely on the workspace of the manipulator in addition to other parameters. In this study, an evolutionary optimization algorithm based on the foraging behaviour of the Escherichia coli bacteria present in the human intestine is utilized to optimize the workspace volume of a 3R manipulator. The new optimization method is modified from the original algorithm for faster convergence. This method is also useful for optimization problems in a highly constrained environment, such as robot workspace optimization. The new approach for workspace optimization of 3R manipulators is tested using three cases. The test results are compared with standard results available using other optimization algorithms, i.e. the differential evolution algorithm, the genetic algorithm and the particle swarm optimization algorithm. The present method is found to be superior to the other methods in terms of computational efficiency.     

Economic dispatch using particle swarm optimization with bacterial foraging effect

This paper presents a novel modified particle swarm optimization (MPSO), which includes advantages of bacterial foraging (BF) and PSO for constrained dynamic economic dispatch (ED) problem. The proposed modified PSO consists of problem dependent four promising values in velocity vector to incorporate repellent advantage of bacterial foraging in PSO for the complex dynamic ED problem. It reliably and accurately tracks a continuously changing solution of the complex cost functions. As there is no differentiation operation in this method, all cost functions can easily be handled. The modified PSO has better balance between local and global search abilities and it can avoid local minima quickly. Finally, a benchmark data set and existing methods are used to show the effectiveness of the proposed method.     

Improved artificial bee colony algorithm based on escaped foraging strategy

This paper presents an improved artificial bee colony algorithm. Under the framework of the basic artificial bee colony algorithm, this paper redefines the artificial bee colony and introduces search strategies for group escape and foraging based on Levy flight. The proposed algorithm is named artificial bee colony algorithm based on escaped foraging strategy (EFSABC).There are different strategies for scout bees, onlookers, and free bees searching for honey sources in the EFSABC: all working bees relinquish old honey sources due to disturbance, and select different routines to seek new honey sources. Sixteen typical high-dimensional standard functions are used to verify the effectiveness of the proposed algorithm. The EFSABC algorithm outperforms the traditional artificial bee colony algorithm in all aspects.     

基于改进混合遗传细菌觅食算法的贝叶斯结构学习算法

针对利用启发式学习算法学习贝叶斯网络时容易陷入局部最优和寻优效率低的问题,提出一种改进的混合遗传细菌觅食优化算法的贝叶斯网络结构学习算法。该算法首先通过遗传算法求得较优种群并作为细菌觅食算法的初始种群;然后利用交叉和变异策略改进细菌觅食算法的复制行为,增加种群多样性,扩大搜索空间;最后通过改进细菌觅食算法的迁移行为的初始化操作更新种群,防止精英个体的丢失。通过种群的迭代搜索最终获得最优的贝叶斯网络结构。实验仿真结果表明,与其他算法相比,该算法的收敛精度和效率有所提升。     

基于细菌觅食的改进蚁群算法

蚁群算法是模仿蚂蚁觅食行为的一种新的仿生学智能优化算法。针对其收敛速度慢和易陷入局部最优的不足,将细菌觅食算法和蚁群算法相结合,提出一种细菌觅食 蚁群算法。在蚁群算法迭代过程中,引入细菌觅食算法的复制操作,以加快算法的收敛速度;引入细菌觅食算法的趋向操作,以增强算法的全局搜索能力。通过经典的旅行商问题和函数优化问题测试表明,细菌觅食 蚁群算法在寻优能力、可靠性、收敛效率和稳定性方面均优于基本蚁群算法及两种改进蚁群算法。     

Location and behavioral effects of lectin binding on entomopathogenic nematodes with different foraging strategies

Lectins have been used to locate and ascribe a function to sensory organs of nematodes. We had two objectives: (1) to determine the location of carbohydrate exudates on the surface of three species of entomopathogenic nematodes with different foraging strategies and (2) to evaluate the importance of carbohydrates in host finding and recognition.Steinernema carpocapsae finds hosts by ambushing, and most individuals respond poorly to host cues. No specific areas of lectin binding were recorded for this species. Wheat germ agglutinin bound specifically to the anterior region ofHeterorhabditis bacteriophora and to the anterior and posterior ofS. glaseri. These two nematode species are cruise foragers and are highly responsive to host cues. The behavioral effects of lectins varied. None of the species' responses to volatile host cues was affected.S. carpocapsae's rate of attachment during ambushing was increased by treatment with WGA, and this effect was negated by treatment with a competing sugar (N-acetylglucosamine). The infectivity ofS. glaseri in an assay that required movement through 5 cm of sand to find the host was significantly decreased by treatment with WGA.