Aircraft robust multidisciplinary design optimization methodology based on fuzzy preference function

This paper presents a Fuzzy Preference Function-based Robust Multidisciplinary Design Optimization(FPF-RMDO) methodology. This method is an effective approach to multidisciplinary systems, which can be used to designer experiences during the design optimization process by fuzzy preference functions. In this study, two optimizations are done for Predator MQ-1 Unmanned Aerial Vehicle(UAV):(A) deterministic optimization and(B) robust optimization. In both problems, minimization of takeoff weight and drag is considered as objective functions, which have been optimized using Non-dominated Sorting Genetic Algorithm(NSGA). In the robust design optimization, cruise altitude and velocity are considered as uncertainties that are modeled by the Monte Carlo Simulation(MCS) method. Aerodynamics, stability and control, mass properties, performance, and center of gravity are used for multidisciplinary analysis. Robust design optimization results show 46% and 42% robustness improvement for takeoff weight and cruise drag relative to optimal design respectively.

Male mate choice in livebearing fishes： an overview

Although the majority of studies on mate choice focus on female mate choice, there is growing recognition of the role of male mate choice too. Male mate choice is tightly linked to 2 other phenomena： female competition for males and ornamentation in females. In the current article, I review the existing literature on this in a group of fishes, Poeciliidae. In this group, male mate choice appears to be based on differences in female quality, especially female size, which is a proxy for fecundity. Some males also have to choose between heterospecific and conspecific females in the unusual mating system of the Amazon molly. In this case, they typically show a preference for conspecific females. Whereas male mate choice is relatively well documented for this family, female ornamentation and female competition are not.

Incipient sexual isolation in Laupala cerasina： Females discriminate population-level divergence in acoustic characters

Sexual selection by female choice can shape the evolution of male traits within populations, since the most attractive males experience an increase in fitness through elevated mating success. Speciation by sexual selection occurs when evolution in traits and preferences within populations causes differentiation among populations, such that females in alternative populations prefer sexual signals of their own population relative to others. Differentiated traits and preferences thereby play an active role in limiting gene flow between divergent populations. The effectiveness of differentiated preferences in maintaining differentiated male signals against the homogenizing effects of gene flow across populations will be limited by both the degree to which fe- males can discriminate against non-local males, and the breeding values of traits and preferences. Populations of the Hawaiian cricket Laupala cerasina have diverged in pulse rate, a sexually selected male signal, and female acoustic preference for pulse rate. Gene flow between neighboring populations may be reduced if migrants from sexually diverged populations experience re- duced mating success. We show that females discriminate among divergent songs characteristic of neighboring populations, that differences among populations in song and preference breed true in a common environment, and that mean preferences for each population closely match the mean pulse rates. Divergence in preference was observed only between populations that also dif- fered in song. Along with a striking ability to discriminate slight differences in song, correlated evolution of song and preference within populations could be a mechanism that promotes assortative mating among populations, thereby reducing gene flow, and leading to speciation in Laupala [Current Zoology 58 （3）： 416-425, 2012].

Mate choice decisions by searchers

For more than two decades rudimentary versions of the fixed sample and sequential search strategies have provided the primary theoretical foundation for the study of mate choice decisions by searchers. The theory that surrounds these models has expanded markedly over this time period. In this paper, we review and extend results derived from these models, with a focus on the empirical analysis of searcher behavior. The basic models are impractical for empirical purposes because they rely on the as- sumption that searchers--and, for applied purposes, researchers--assess prospective mates based on their quality, the fitness consequences of mate choice decisions. Here we expound versions of the models that are more empirically useful, reformulated to reflect decisions based on male phenotypic characters. For some organisms, it may be possible to use preference functions to de- rive predictions from the reformulated models and thereby avoid difficulties associated with the measurement of male quality per se. But predictions derived from the two models are difficult to differentiate empirically, regardless of how the models are formu- lated. Here we develop ideas that illustrate how this goal might be accomplished. In addition, we clarify how the variability of male quality should be evaluated and we extend what is known about how this variability influences searcher behavior under each model. More general difficulties associated with the empirical study of mate choice decisions by searchers are also discussed [Current Zoology 59 （2）： 184-199, 2013].

Discovering admissible Web services with uncertain QoS

Open and dynamic environments lead to inher- ent uncertainty of Web service QoS （Quality of Service）, and the QoS-aware service selection problem can be looked upon as a decision problem under uncertainty. We use an empiri- cal distribution function to describe the uncertainty of scores obtained from historical transactions. We then propose an approach to discovering the admissible set of services in- cluding alternative services that are not dominated by any other alternatives according to the expected utility criterion. Stochastic dominance （SD） rules are used to compare two services with uncertain scores regardless of the distribution form of their uncertain scores. By using the properties of SD rules, an algorithm is developed to reduce the number of SD tests, by which the admissible services can be reported pro- gressively. We prove that the proposed algorithm can be run on partitioned or incremental alternative services. Moreover, we achieve some useful theoretical conclusions for correct pruning of unnecessary calculations and comparisons in each SD test, by which the efficiency of the SD tests can be im- proved. We make a comprehensive experimental study using real datasets to evaluate the effectiveness, efficiency, and scal- ability of the proposed algorithm.