Dynamic averaging and foraging decisions in horses (Equus callabus).

The variability of most environments taxes foraging decisions by increasing the uncertainty of the information available. One solution to the problem is to use dynamic averaging, as do some granivores and carnivores. Arguably, the same strategy could be useful for grazing herbivores, even though their food renews and is more homogeneously distributed. Horses (Equus callabus) were given choices between variable patches after short or long delays. When patch information was current, horses returned to the patch that was recently best, whereas those without current information matched choices to the long-term average values of the patches. These results demonstrate that a grazing species uses dynamic averaging and indicate that, like granivores and carnivores, they can use temporal weighting to optimize foraging decisions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于细菌觅食机理改进粒子群算法的研究

粒子群算法与细菌觅食算法在优化问题中均体现了较好的性能,但由于各自特定的进化机制,也都存在缺点。粒子群优化（PSO）算法在优化过程中过快陷入局部极值,为了避免这个缺陷,提出了一种新的混合算法。通过PSO算法完成整个空间的全局搜索,通过细菌觅食算法（BFOA）中的趋向性运动算子完成局部搜索的功能,再通过典型函数进行测试,结果表明新算法可以有效弥补细菌觅食算法速度不快和粒子群算法精度不高的缺陷,同时部分地避免了局部收敛的问题,从而适用于解决复杂函数的优化问题。     

An improved bacterial foraging algorithm for combined static/dynamic environmental economic dispatch

Economic dispatch is carried out at the energy control center to find out the optimal output of thermal generating units such that power balance criterion is met, unit operating limits are satisfied and the fuel cost is minimized. With growing environmental awareness and strict government regulations throughout the world, it has become essential to optimize not only the total fuel cost but also the harmful emissions, both, under static as well as dynamic conditions. The static environment economic dispatch finds the optimal output of generating units for a fixed load demand at a given time, while the dynamic environmental economic dispatch schedules the output of online generators with changing power demands over a certain time period (normally one day) so as to minimize these two conflicting objectives, simultaneously. In this paper, the price penalty factor approach is employed for simultaneous minimization of cost and emission. The generator ramp rate constraints, non-convex and discontinuous nature of cost function and the large number of generators in practical power plants, make this problem very difficult to solve. Here, a fuzzy ranking approach is employed to identify the solution which offers the best compromise between cost and emission objectives.     

离散型细菌觅食算法求解TSP

旅行商问题(TSP)是组合优化问题的典型代表,针对TSP的求解提出一种离散型细菌觅食(DBFO)算法.该算法通过结合2-opt算法设计了一种适合处理离散型变量的趋化算子,将细菌觅食算法推广到了离散情形.同时,结合TSP的特点,在迁徙算子中引入基因库的思想来指导新个体的生成,提高了算法的搜索效率.通过对TSPLIB标准库中22个实例进行仿真实验.实验结果表明,该算法能够有效求解城市规模500以下的TSP,与混合蚁群算法和离散型萤火虫群算法相比,具有更好的全局收敛性和稳定性.     

基于细菌觅食优化算法的WSNs节点部署策略

为了提高传感器节点的有效覆盖率,提出了一种基于细菌觅食优化(BFO)算法的节点部署策略。以网络覆盖率为目标函数,在细菌觅食算法的趋向操作过程中,引入碰壁策略,对细菌初始位置进行优化,从而提高算法的收敛速度。算法中的每个细菌都代表一只传感器,多个细菌组成的一个菌落代表一种传感器的部署方案。算法以菌落为单位做复制操作和迁徙操作,按照菌落适应度值大小选出较为优越的部署方案。通过仿真实验,分析了参数对算法性能的影响,并与其他方法的优化结果进行比较,结果表明:该算法有效地提高了传感器节点覆盖率。     

改进的细菌觅食优化算法

细菌觅食优化算法是一种受大肠杆菌觅食现象启发产生的一种群体进化算法,该算法具有良好的全局优化能力,鲁棒性强,算法简单等优点,但其也存在易早熟,收敛速度慢等缺点. 根据其缺点,提出了一种改进的细菌觅食优化算法,改进后的算法收敛速度加快,在一定程度上避免了易早熟的缺点. 将原算法和改进算法应用于PID参数的在线自整定,通过matlab仿真实验证明了算法改进后的优越性.     

Response to walnut olfactory and visual cues by the parasitic wasp Diachasmimorpha juglandis

Diachasmimorpha juglandis is a specialist parasitoid attacking fly larvae in the genus Rhagoletis that feed exclusively on walnut fruit husks. In a free-foraging assay comparing response to uninfested, infested, and mechanically damaged fruits, we first determined that D. juglandis use host feeding damage on the fruit as a cue for host presence. In another free-foraging assay that used artificial walnut models and wind tunnel experiments, D. juglandis distinguished infested from uninfested fruits by using either olfactory or visual cues separately. However, the response rate of wasps in the wind tunnel was raised considerably when visual cues were also available. We analyzed the volatile compounds emitted by cohorts of uninfested, mechanically damaged, and infested fruits 1, 3, 5, 8, and 10 days after oviposition by flies into the infested fruits. Total volatile emissions did not differ significantly among treatments, but quantitative changes in volatiles distinguished infested fruits from uninfested and damaged fruits. The fact that parasitoids did not distinguish between infested and damaged fruits in assays where damage was visible indicates that they rely on visual cues when those are available.     

改进的细菌觅食优化算法求解0-1背包问题

细菌觅食优化算法作为一种新兴的智能优化算法,一般用来解决连续域的问题。为了解决离散域问题,提出了一种改进的细菌觅食优化算法。采用线性递减的思想和随机的游动长度代替固定步长和随机游动方向,改进了趋向性操作方案,并将其应用于解决0-1背包问题。将改进的细菌觅食优化算法与遗传算法、离散粒子群优化算法及基本的离散化细菌觅食优化算法分别在小规模和大规模的0-1背包问题上进行了仿真比较,表明了改进的细菌觅食优化算法能取得较好的效果,寻优能力强。     

Effects of molasses grass,Melinis minutiflora volatiles on the foraging behavior of the cereal stemborer parasitoid,Cotesia sesamiae

Olfactory responses of the cereal stemborer parasitoid Cotesia sesamiae to volatiles emitted by gramineous host and nonhost plants of the stemborers were studied in a Y-tube olfactometer. The host plants were maize (Zea mays) and sorghum ( Sorghum bicolor), while the nonhost plant was molasses grass (Melinis minutiflora). In single-choice tests, females of C. sesamiae chose volatiles from infested and uninfested host plants and molasses grass over volatiles from the control (soil). In dual-choice tests, the wasp preferred volatiles from infested host plants to those from uninfested host plants. There was no discrimination between molasses grass volatiles and those of uninfested maize, uninfested sorghum, or infested maize. The wasp preferred sorghum volatiles over maize. Combining uninfested maize or sorghum with molasses grass did not make volatiles from the combination more attractive as compared to only uninfested host plants. Infested maize alone was as attractive as when combined with molasses grass. Infested sorghum was preferred over its combination with molasses grass. Local growth conditions of the molasses grasses influenced attractiveness to the parasitoids. Volatiles from Thika molasses grass were attractive, while those from Mbita molasses grass were not. Growing the Thika molasses grass in Mbita rendered it unattractive and vice versa with the Mbita molasses grass. This is a case of the same genotype expressing different phenotypes due to environmental factors.     

基于Levy飞行的改进菌群觅食算法

针对经典菌群觅食算法因固定趋化步长导致的求解精度不高、收敛性能差等缺陷,提出一种基于Levy飞行的菌群觅食算法,其特点是利用基于Levy分布的趋化步长改善算法的求解精度与收敛性能,借助Levy飞行随机游走策略改善细菌迁徙位置.多个基准测试函数的实验结果表明,该算法在求解质量和收敛性能上均取得了较好的改进效果.