A volume‐consistent discrete formulation of aggregation population balance equations

In this paper, a new finite volume scheme for the numerical solution of the pure aggregation population balance equation, or Smoluchowski equation, on non‐uniform meshes is derived. The main feature of the new method is its simple mathematical structure and high accuracy with respect to the number density distribution as well as its moments. The new method is compared with the existing schemes given by Filbet and Laurençot (SIAM J. Sci. Comput., 25 (2004), pp. 2004–2028) and Forestier and Mancini (SIAM J. Sci. Comput., 34 (2012), pp. B840–B860) for selected benchmark problems. It is shown that the new scheme preserves all the advantages of a conventional finite volume scheme and predicts higher‐order moments as well as number density distribution with high accuracy. Copyright © 2015 John Wiley & Sons, Ltd.     

Evolutionary games

This paper deals with a mathematical game. As the name implies, the game concept is formulated with biological evolution in mind. An evolutionary game differs from the usual game concepts in that the players cannot choose their strategies. Rather, the strategies used by the players are handed down from generation to generation. It is the survival characteristics of a strategy that determine the outcome of the evolutionary game. Players interact and receive payoffs according to the strategies they are using. These interactions, in turn, determine the fitness of players using a given strategy. The survival characteristics of strategy are determined directly from the fitness functions. Necessary conditions for determining an evolutionarily stable strategy are developed here for a continuous game. Results are illustrated with an example.Dedicated to G. LeitmannThis work was supported by NSF Grant No. INT-82-10803 and The University of Western Australia (Visiting Fellowship, Department of Mathematics, 1983).     

A MODEL OF CHINOOK SALMON POPULATION DYNAMICS INCORPORATING SIZE‐SELECTIVE EXPLOITATION AND INHERITANCE OF POLYGENIC CORRELATED TRAITS

Abstract Concern regarding the potential for selective fisheries to degrade desirable characteristics of exploited fish populations is growing worldwide. Although the occurrence of fishery‐induced evolution in a wild population has not been irrefutably documented, considerable theoretical and empirical evidence for that possibility exists. Environmental conditions influence survival and growth in many species and may mask comparatively subtle trends induced by selective exploitation, especially given the evolutionarily short time series of data available from many fisheries. Modeling may be the most efficient investigative tool under such conditions. Motivated by public concern that large‐mesh gillnet fisheries may be altering Chinook salmon in western Alaska, we constructed a stochastic model of the population dynamics of Chinook salmon. The model contained several individually based components and incorporated size‐selective exploitation, assortative mating, size‐dependent female fecundity, density‐dependent survival, and the heritability of size and age. Substantial reductions in mean size and age were observed under all scenarios. Concurrently reducing directional selection and increasing spawning abundance was most effective in stimulating population recovery. Use of this model has potential to improve our ability to investigate the consequences of selective exploitation and aid development of improved management strategies to more effectively sustain fish and fisheries into the future.     

INACCESSIBLE CONTINUOUSLY STABLE STRATEGIES

ABSTRACT. The evolutionary stability concepts continuously stable strategies (CSS) and evolutionarily stable neighborhood invader strategies (ESNIS) share two properties in common. First, they are both evolutionarily stable strategies (ESS). Secondly, given any strategy in the close neighborhood of the CSS or ESNIS, there are some strategies that are closer to the CSS or ESNIS that can invade it. An ESNIS is a CSS but the converse is not true in general. We examine evolutionary adaptive dynamics in the neighborhood of a CSS that is not an ESNIS. We show that if an evolutionary game possesses a CSS which is not an ESNIS, the succession of strategies mediated by natural selection become arbitrarily close to the CSS but the precise value of the CSS cannot be attained unless the CSS is the first strategy to invade into the environment and is henceforth never perturbed. Thus if evolution does not start with the CSS that is not an ESNIS, we will have a phenomenon of bounded evolutionary succession that does not come to an end. The analysis is applied to a class of monomorphic population evolutionary game models in which species ecological interaction is modeled by the Lotka‐Volterra equations.     

Time development of a Markov process in a finite population: Application to diffusion of information

A systematic procedure of truncating the hierarchy of moment equations describing the stochastic evolution of a Markov process in a finite population is developed. The procedure makes use of the asymptotic expression for a certain higher‐order moment of the relevant probability distribution and yields finite‐size corrections to all lower‐order moments. The usefulness of the method is illustrated by applying it to study the mean and the variance of the stochastic variable n(t), the number of active spreaders at time t, in Bartholomew's model of diffusion of information. The results thus obtained are compared with the ones following from the exact probability distribution for the model (wherever known) and the agreement between the two sets of results is found to be remarkably good.     

Colony and evolutionary dynamics of a two‐stage model with brood cannibalism and division of labor in social insects

Division of labor (DOL) is a major factor for the great success of social insects because it increases the efficiency of a social group where different individuals perform different tasks repeatedly and presumably with increased performance. Cannibalism plays an important role in regulating colony growth and development by regulating the number of individuals in a colony and increasing survival by providing access to essential nutrients and minimizing competition among colony mates. To understand the synergy effects of DOL and cannibalistic behavior on colony dynamic outcomes, we propose and study a compartmental two‐stage model using ecological and evolutionary game theory settings. Our analytical results of the ecological and evolutionary models suggest that: (1) A noncannibalistic colony can survive if the efficiency of energy investment reflecting the DOL is greater than the relative death rate of the older population. (2) A cannibalistic colony can die out if both the efficiency of energy investment and the relative cannibalism rate (where each is also reflecting the DOL) are too large; or if the relative cannibalism rate alone is too small. (3) From our numerical analysis, cannibalism can increase or reduce the colony's total population size, which greatly depends on the benefit of egg cannibalism increasing or decreasing of adult's lifespan. (4) A cannibalistic and noncannibalistic colony can experience bistability due to cooperative behavior. (5) In the evolutionary settings, DOL can prevent colony death and natural selection can preserve strong Allee effects by selecting the traits with the largest investment on brood care and the lowest cannibalism rate. (6) Evolutionary dynamics may increase the fitness of the colony, i.e., the successful production of workforce which results in the increase of total worker population size, colony survival, and reproduction. Our results suggest both cannibalism and DOLs are adaptive strategies that increase the size of the worker population, and therefore, persistence of the colony.     

On the convergence of a factorized distribution algorithm with truncation selection

We investigate the global convergence of a factorized distribution algorithm (FDA) with truncation selection. Like conventional genetic algorithms, FDAs maintain and successively improve a population of solutions. In FDAs, a distribution model is built based on the statistical information extracted from a set of selected solutions in the current population, and then the model thus built is used to generate new solutions for the next generation. The variable‐dependence structure of the distribution model in FDAs is determined by the variable‐interaction structure of the objective function. We prove that the FDA with truncation selection converges globally for optimization of a class of additively decomposable functions (ADF). Our results imply that the utilization of appropriately selected dependence relationships is sufficient to guarantee the global convergence of estimation of distribution algorithms (EDAs) for optimization of ADFs. © 2004 Wiley Periodicals, Inc. Complexity 9: 17–23, 2004     

Minimizing coherent risk measures of shortfall in discrete‐time models with cone constraints

The paper studies the problem of minimizing coherent risk measures of shortfall for general discrete‐time financial models with cone‐constrained trading strategies, as developed by Pham and Touzi. It is shown that the optimal strategy is obtained by super‐hedging a contingent claim, which is represented as a Neyman–Pearson‐type random variable.     

AN INDIVIDUAL‐BASED MODEL FOR TRADITIONAL FORAGING BEHAVIOR: INVESTIGATING EFFECTS OF ENVIRONMENTAL FLUCTUATION

Abstract We present an individual‐based model to simulate the evolution of traditional foraging strategies in a fluctuating environment. The parameters and procedures are based on observed behavior of barnacle geese, Branta leucopsis, during spring staging off the coast of Helgeland, Norway. Within a temporally and spatially heterogeneous environment, goose movement is modeled according to state‐dependent site selection decisions that maximize food intake. The aim of each individual is to optimize fitness (survival and reproduction) by gaining enough food (energy reserves) during 3 weeks of foraging to meet a threshold of energy necessary for successful reproduction. The geese return to the same islands each year and on a daily basis choose unoccupied sites according to their rank in the population‐structured dominance hierarchy, memories of previously visited sites (tradition), past reproductive success, inherited genetic influence towards site faithfulness and/or site quality, and knowledge of the available biomass density. It is assumed that with each subsequent return to a specific location, increased familiarity of the area will benefit an individual through greater food acquisition by more efficient foraging practices. In the event of variable environmental conditions, geese are faced with a critical decision to return to previously visited sites or abandon tradition to explore for something better. It is shown that habitat quality plays an integral role in population dynamics. Beyond the scope of this paper, the evolution of foraging strategies that directly affect reproductive potential is shown to inevitably determine the resilience of the population over time ( Kanarek [2006] ). Further experiments are required for detailed results and analysis of specific circumstances that provoke the adaptation of certain behaviors. In general, this modeling approach has the potential to reveal significant insight into the emergence of stable responses to environmental disturbance.     

基于种群自适应调整的多目标差分进化算法

为提高已有多目标进化算法在求解复杂多目标优化问题上的收敛性和解集分布性,提出一种基于种群自适应调整的多目标差分进化算法。该算法设计一个种群扩增策略,它在决策空间生成一些新个体帮助搜索更优的非支配解;设计了一个种群收缩策略,它依据对非支配解集的贡献程度淘汰较差的个体以减少计算负荷,并预留一些空间给新的带有种群多样性的扰动个体;引入精英学习策略,防止算法陷入局部收敛。通过典型的多目标优化函数对算法进行测试验证,结果表明所提算法相对于其他算法具有明显的优势,其性能优越,能够在保证良好收敛性的同时,使获得的Pareto最优解集具有更均匀的分布性和更广的覆盖范围,尤其适合于高维复杂多目标优化问题的求解。     

A large population job search game with discrete time

A job search problem is considered, in which there is a large population of jobs initially available and a large population of searchers. The ratio of the number of searchers to the number of jobs is α. Each job has an associated value from a known distribution. At each of N moments the searchers observe a job, whose value comes from the distribution of the values of currently available jobs. If a searcher accepts a job, s/he ceases searching and the job becomes unavailable. Hence, the distribution of the values of available jobs changes over time. Also, the ratio of the number of those still searching to the number of available jobs changes. The model is presented and Nash equilibrium strategies for such problems are considered. By definition, when all the population use a Nash equilibrium strategy, the optimal response of an individual is to use the same strategy. Conditions are given that ensure the existence of a unique Nash equilibrium strategy. Examples are given to illustrate the model and present different approaches to solving such problems.     

Reservoir storage with skew inflows

The storage problem for infinite reservoirs where annual inflows are distributed as independent gamma variables is treated in this paper. After having determined the distribution of the water content in the reservoir under consideration for a given period, an attempt was made to derive the expressions for the first four moments of the surplus and deficit, and then to approximate their distributions by the Type I curve using the Pearson criterion. The expected value of the range was also derived, and its variance was approximated by a linear equation of the reservoir life. Finally, the distribution of the range was approximated by the Type III curve.     

Bivariate Distributions with Pearson Type VII Conditionals

In this article the most general class of bivariate distributions such that both conditional densities are Pearson Type VII, with fixed shape parameter, is fully characterized. Some of its properties and relations with other distributions are explored. The estimation of parameters is considered by the methods of maximum likelihood and pseudolikelihood and a method for random variate generation is presented along with a simulation experiment. Bivariate and multivariate extensions of the Pearson Type VII conditionals distribution are also discussed.     

Dynamics of a single species evolutionary model with Allee effects

We investigate the evolutionary outcomes of a single species population subject to Allee effects within the framework of a continuous strategy evolutionary game theory (EGT) model. Our model assumes a single trait creates a phenotypic trade-off between carrying capacity (i.e., competition) and predator evasion ability following a Gaussian distribution. This assumption contributes to one of our interesting findings that evolution prevents extinction even when population exhibits strong Allee effects. However, the extinction equilibrium can be an ESS under some special distributions of anti-predation phenotypes. The ratio of variation in competition and anti-predation phenotypes plays an important role in determining global dynamics of our EGT model: (a) evolution may suppress strong Allee effects for large values of this ratio; (b) evolution may preserve strong Allee effects for small values of this ratio by generating a low density evolutionary stable strategy (ESS) equilibrium which can serve as a potential Allee threshold; and (c) intermediate values of this ratio can result in multiple ESS equilibria.     

On the internal path length of d‐dimensional quad trees

It is proved that the internal path length of a d‐dimensional quad tree after normalization converges in distribution. The limiting distribution is characterized as a fixed point of a random affine operator. We obtain convergence of all moments and of the Laplace transforms. The moments of the limiting distribution can be evaluated from the recursion and lead to first order asymptotics for the moments of the internal path lengths. The analysis is based on the contraction method. In the final part of the paper we state similar results for general split tree models if the expectation of the path length has a similar expansion as in the case of quad trees. This applies in particular to the m‐ary search trees. ©1999 John Wiley & Sons, Inc. Random Struct. Alg., 5: 25–41, 1999     

两人进化博弈策略的决定机制与应用研究

通过建立一般情况下的两人进化博弈模型,给出了系统均衡点对应的矩阵行列式和迹表达式的经济含义,分析了16种典型情形下的进化稳定策略,详细讨论了均衡点稳定性分析结果所对应的博弈双方决策过程,从策略权衡的视角揭示了策略选择的内在机制。研究结果表明:不同策略前提下的相对净支付决定了系统的进化稳定策略,对方的策略选择以及自身可选策略的支付比较是影响博弈主体策略选择的两个基本要素,博弈主体会趋向于选择在对方策略既定下能够带来更大支付的策略。最后以环境治理中地方政府与企业以及地方政府之间的博弈关系为例,从对称博弈和非对称博弈两方面阐明了本文所构建模型在政策设计中的应用价值:针对不同案例,只要明确了两人博弈的支付矩阵,就可以通过计算相对净支付确定博弈双方的行为演化规律和稳定策略,从而简化计算过程,更加直接和更为便捷地为政策设计提供理论参考。     

Asymptotics of Ruin Probabilities for Risk Processes under Optimal Reinsurance and Investment Policies: The Large Claim Case

In a classical risk process reinsurance and investment can be chosen at any time. We find the Lundberg exponent and the Cramér–Lundberg approximation for the ruin probability under the optimal strategy in the case where no exponential moments for the claim size distribution exist. We also show that the optimal strategies converge.     

Some Truncated Bivariate Distributions

Truncated versions of the bivariate generalized Pareto, bivariate inverted dirichlet and the bivariate Pearson type VII distributions are introduced. Unlike the un-truncated versions, these possess finite moments of all orders and could therefore be better models for certain practical situations. Explicit expressions for the moments are derived for each of the truncated distribution.     

Genetic algorithms with shrinking population size

A Genetic Algorithm (GA) is an evolutionary computation technique inspired by the principle of biological evolution via natural selection. It employs the fundamental components of evolution, such as selection, mating, and mutation, which continue from generation to generation, creating better solutions as time progresses. Although it is mostly used as an optimization tool, GA enjoys a wide spectrum of applications in diverse fields such as engineering, medicine, and ecology, among others. In this study, we propose three different population size reduction methods for a typical GA optimization, aiming to increase efficiency. Additionally, we compare the accuracy and precision of these methods using Monte Carlo simulations.