Collective foraging in heterogeneous landscapes

Animals foraging alone are hypothesized to optimize the encounter rates with resources through Lévy walks. However, the issue of how the interactions between multiple foragers influence their search efficiency is still not completely understood. To address this, we consider a model to study the optimal strategy for a group of foragers searching for targets distributed heterogeneously. In our model, foragers move on a square lattice containing immobile but regenerative targets. At any instant, a forager is able to detect only those targets that happen to be in the same site. However, we allow the foragers to have information about the state of other foragers. A forager who has not detected any target walks towards the nearest location, where another forager has detected a target, with a probability exp(−αd), where d is the distance between the foragers and α is a parameter characterizing the propensity of the foragers to aggregate. The model reveals that neither overcrowding (α → 0) nor independent searching (α → ∞) is beneficial for the foragers. For a patchy distribution of targets, the efficiency is maximum for intermediate values of α. In addition, in the limit α → 0, the length of the walks can become scale-free.     

盐水方肠的品质优化

通过单因素和正交试验,确定大豆分离蛋白、大豆组织蛋白和卡拉胶在盐水方肠中的最适添加比例分别为22%、15%和0.99%。     

湿陷性黄土地区地基的施工方法

结合具体工程实例,介绍了湿陷性黄土地区的地基处理方法,分别阐述了施工方案,施工步骤及操作要点,并指出施工过程中的相关注意事项,以期指导实践,保证湿陷性黄土地基施工质量。     

Optimal control with constrained total variance for Markov jump linear systems with multiplicative noises

We consider in this paper the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noises (MJLS-mn for short). Our objective is to present an optimal policy for the problem of maximising the system's total expected output over a finite-time horizon while restricting the weighted sum of its variance to a pre-specified upper-bound value. We obtain explicit conditions for the existence of an optimal control law for this problem as well as an algorithm for obtaining it, extending previous results in the literature. The paper is concluded by applying our results to a portfolio selection problem subject to regime switching.     

基于非恒定流模型的山洪沟水面线计算

本文将具有良好激波捕捉能力的Godunov格式离散圣维南方程组建立的一维非恒定流模型用于山洪沟水面线的分析计算。首先通过混合流算例验证了该模型具有良好的模拟间断水面和流态过渡的能力,随后将该非恒定流模型用于刘家舍窠山洪沟、梁家岔山洪沟和红花坪山洪沟的水面线计算。分析认为计算结果合理,模型较好地模拟了陡坡和断面变化剧烈情况下出现的急流和流态过渡等问题。该模型在山洪沟水面线的分析计算领域具有良好的工程应用前景。     

梧州市平浪防洪堤总体设计方案选择

介绍了梧州市平浪防洪堤堤线、堤型的选择原则、思路,总体设计方案等基本情况。该设计方案融入可持续发展及生态水利的理念,将环保、人文以及可持续发展等贯彻于设计的全过程,体现了人与自然的和谐共处。     

Buoyancy effects on the laminar boundary layer heat transfer along vertically moving cylinders

Abstract

The effects of buoyancy forces on the laminar boundary layer flow and heat transfer along vertically moving cylinders are analyzed for the cases of prescribed surface temperature and prescribed wall heat flux in power of streamwise distance. Local similarity solutions are obtained to show the effects of buoyancy parameters and the transverse curvature of the cylinder on the surface friction and heat transfer rate.     

Cyclical parthenogenesis algorithm for layout optimization of truss structures with frequency constraints

Structural optimization with frequency constraints is seen as a challenging problem because it is associated with highly nonlinear, discontinuous and non-convex search spaces consisting of several local optima. Therefore, competent optimization algorithms are essential for addressing these problems. In this article, a newly developed metaheuristic method called the cyclical parthenogenesis algorithm (CPA) is used for layout optimization of truss structures subjected to frequency constraints. CPA is a nature-inspired, population-based metaheuristic algorithm, which imitates the reproductive and social behaviour of some animal species such as aphids, which alternate between sexual and asexual reproduction. The efficiency of the CPA is validated using four numerical examples.     

ASRSM: A Sequential Experimental Design for Response Surface Optimization

Most preset response surface methodology (RSM) designs offer ease of implementation and good performance over a wide range of process and design optimization applications. These designs often lack the ability to adapt the design on the basis of the characteristics of application and experimental space so as to reduce the number of experiments necessary. Hence, they are not cost‐effective for applications where the cost of experimentation is high or when the experimentation resources are limited. In this paper, we present an adaptive sequential response surface methodology (ASRSM) for industrial experiments with high experimentation cost, limited experimental resources, and high design optimization performance requirement. The proposed approach is a sequential adaptive experimentation approach that combines concepts from nonlinear optimization, design of experiments, and response surface optimization. The ASRSM uses the information gained from the previous experiments to design the subsequent experiment by simultaneously reducing the region of interest and identifying factor combinations for new experiments. Its major advantage is the experimentation efficiency such that for a given response target, it identifies the input factor combination (or containing region) in less number of experiments than the classical single‐shot RSM designs. Through extensive simulated experiments and real‐world case studies, we show that the proposed ASRSM method outperforms the popular central composite design method and compares favorably with optimal designs. Copyright © 2012 John Wiley & Sons, Ltd.