Optimal Population Size Research Articles

Economies of Scale in Local Government: General Government Spending

The purpose of this paper is to determine whether larger or smaller municipalities are more efficient in their levels of overhead costs. The operative measure is per capita annual costs for these services. In addition, the issue of market structure as a factor in these costs is also to be studied. It is not for the purpose of considering costs for specific services but rather the general overhead items that are required of all local governments. The method of study will be to use the cities and towns of New York State over a number of years. This will ensure that the study group is relatively homogeneous over applicable state laws as well as giving a wide variation in the population levels studied. The per capita expenditures will be regressed against population and market power variables using several equation forms. The results will be tested for significance in scale effects and market power effects. Optimal population sizes will be calculated where possible. The outline of the paper is as follows: 1) Introduction, 2) Background issues, 3) The study design, 4) Data, 5) Results, and 6) Conclusions.

Revisiting the Optimal Population Size Problem under Endogenous Growth: Minimal Utility Level and Finite Life

In this paper, we devise a social criterion in the spirit of the critical utility level of Blackorby-Donaldson (1984) to study an optimal population size problem in an endogenously growing economy populated by workers living a fixed amount of time and without capital accumulation. Population growth is endogenous. The problem is analytically solved, yielding closed-form solutions to optimal demographic and economic dynamics. It is shown that provided the economy is not driven to optimal finite time extinction, the optimal solution is egalitarian for appropriate choices of the critical utility levels: all individuals of any cohort are given the same consumption. The results obtained do not require any priori restriction of the values of the elasticity of intertemporal substitution unlike in several related papers.

A New Approach to Population Sizing for Memetic Algorithms: A Case Study for the Multidimensional Assignment Problem

Memetic algorithms are known to be a powerful technique in solving hard optimization problems. To design a memetic algorithm, one needs to make a host of decisions. Selecting the population size is one of the most important among them. Most of the algorithms in the literature fix the population size to a certain constant value. This reduces the algorithm's quality since the optimal population size varies for different instances, local search procedures, and runtimes. In this paper we propose an adjustable population size. It is calculated as a function of the runtime of the whole algorithm and the average runtime of the local search for the given instance. Note that in many applications the runtime of a heuristic should be limited and, therefore, we use this bound as a parameter of the algorithm. The average runtime of the local search procedure is measured during the algorithm's run. Some coefficients which are independent of the instance and the local search are to be tuned at the design time; we provide a procedure to find these coefficients. The proposed approach was used to develop a memetic algorithm for the multidimensional assignment problem (MAP). We show that our adjustable population size makes the algorithm flexible to perform efficiently for a wide range of running times and local searches and this does not require any additional tuning of the algorithm.

An Investigation into the Use of Intelligent Systems for Currency Trading

Investors use a number of technical trading tools to help them in their decision-making. This article aims to enhance this decision making process through the application of Genetic Algorithms (GAs) and Artificial Neural Networks (ANNs). The signals generated by technical trading tools are optimised for maximum profit through the use of GAs. The optimised signals are fed into a variety of fully connected feed forward ANNs, which combine these signals and output a single set of signals of whether to buy, hold or sell in the current market state. The different solutions produced are compared and contrasted, to determine the best ANN architecture for this type of signal amalgamation problem, and the optimal population size and mutation function for the GA. The result is an autonomous trading system with intelligence. This system, as described in this article, has proven to be profitable based on data presented to it--which spans ten currencies over a five year period. The profit margins are statistically significant when compared to un-optimised trading rules as suggested by literature. Further, the margins are statistically significantly more profitable than other no-risk investment strategies.

Optimum Population Size of Indigenous P-solubilizing Bacteria to Correct P Availability in Acid Soils

Ultisols and Inceptisols were used to investigate the adsorption-desorption capacity of P and the effect of organic matter on the dynamics of P availability in tropical acid soils. The experiment consisted of two sub-experiments. Sub-experiment I was to study the adsorption-desorption capacity of Ultisols, Fresh-water lowland Inceptisols, and tidal-swamp Inceptisols. Therefore, surface soils (0 to 30 cm) of each tested soil were treated with 0, 10, 20, 30, 40, 60, 80, 100, 120, 140, 170, and 200 mg P kg-1 of soil. Sub-experiment II was to study the effects of organic matter application (0, 5, 10, and 15 Mg ha-1) on the dynamics of available P following 60d incubation under room temperature. P fertilizer application significantly affected water soluble-P (WSP) (p<0.01) and soil available P-Bray and Kurtz No. 1 (BKP) (p<0.01) in the three tested soils. The different response of both WSP and BKP confirmed that the soils tested in the current experiment had different soil P buffering capacity in the order of Tidal-lowland Inceptisol>Upland Ultisol>fresh-water Lowland Inceptisol. OM application increased the BKP in all tested soils as compared to the control. Differences in pattern of soil available P dynamics over time were detected between upland soil and two lowland soils used in the current experiment. Keywords: Adsorption-desorption, Inceptisols, organic matter, Ultisols

Litter Production and Decomposition Rate in the Reclaimed Mined Land under Albizia and Sesbania Stands and Their Effects on some Soil Chemical Properties

Indonesian acid soils were used to determine an optimum population size of indigenous P-solubilizing bacteria (PSB) for solubilizating fixed P. The experiment consisted of two sub-experiments. Sub-experiment I was to isolate the indigenous PSB from Ultisols, Fresh-water lowland Inceptisols, and tidal-swamp Inceptisols. Subexpriment II was to study the capacity of the isolated PSB to correct P availability in acid soils by inoculating the isolated PSB into the tested soils at 0, 105, 1010, and 1015 cells. The population of the indigenous PSB in the tested soils increased as a result of the inoculation. Both Al-P and Fe-P content in the three tested soils decreased as compared with the initial content. The increases of available P were significantly correlated with the decreases both in Al-P (r2 = 0.68 for the Ultisols; r2 = 0.51 for the fresh-water Inceptisols; and r2 = 0.35 for the tidal-swamp Inceptisols) and in Fe-P (r2 = 0.91 for the Ultisols; r2 = 0.45 for the fresh-water lowland Inceptisols; and r2 = 0.78 for the tidal-swamp Inceptisols). The increases of available P were significantly correlated with the increases of the population of the PSB (r2 = 0.60 for the Ultisols; r2 = 0.55 for the fresh-water lowland Inceptisols; and r2 = 0.69 for the tidal-swamp Inceptisols). The available P in the three tested soils sharply increased if the population size of the PSB was about 1 × 109 cfu g-1 of soil. Keywords: Al-P, Fe-P, fresh-water lowland, isolated, Pikovskaya medium, tidal swamp

Diversity of efficient coding solutions for a population of noisy linear neurons

Methods E cient coding posits that neural resources (cost) should e ciently be utilized for signal representation (objective). (5, 14) • Dependency on the objective function has been well examined. (13, 6, 8) • Dependency on the cost function: For a single neuron: output range, ring rate, or variance constraints. (11, 4, 14) For multiple neurons: less studied. We examine the e ects of costs that are likely to be relevant in neural populations.

EvAg: a scalable peer-to-peer evolutionary algorithm

This paper studies the scalability of an Evolutionary Algorithm (EA) whose population is structured by means of a gossiping protocol and where the evolutionary operators act exclusively within the local neighborhoods. This makes the algorithm inherently suited for parallel execution in a peer-to-peer fashion which, in turn, offers great advantages when dealing with computationally expensive problems because distributed execution implies massive scalability. In this paper we show another advantage of this algorithm: We experimentally demonstrate that it scales up better than traditional alternatives even when executed in a sequential fashion. In particular, we analyze the behavior of several EAs on well-known deceptive trap functions with varying sizes and levels of deceptiveness. The results show that the new EA requires smaller optimal population sizes and fewer fitness evaluations to reach solutions. The relative advantage of the new EA is more outstanding as problem hardness and size increase. In some cases the new algorithm reduces the computational efforts of the traditional EAs by several orders of magnitude.

The Role of Ecological and Economic Factors in the Management of a Spatially Structured Moose Alces alces Population

We present a bioeconomic model for moose Alces alces management in Norway, where two sub‐populations of moose are subject to different site‐specific mortality rates caused by the spatial distribution of territorial wolf Canis lupus packs, and are coupled by the seasonal migration of moose. The costs and benefits of moose are asymmetrically distributed in space, since they congregate in the wolf territory during winter where most browsing damage occurs. Using a class‐structured matrix population model as the basis for bioeconomic analysis, we investigated how the optimal moose management differed between a unified (i.e. maximising overall profit) and a non‐unified (i.e. profit maximised at the level of individual landowners) management scheme. Within the unified management scheme, the combined marginal costs and benefits decide the optimal off‐take rate, and the relative hunting value and damage costs decide the relative allocation of the harvest between the two sub‐populations. In the non‐unified management scheme, harvesting takes place up to the point where the private marginal hunting value equals the private marginal browsing cost, while the relative hunting value and damage costs do not influence the optimal management. As the browsing damage that occurs inside the wolf territory is not taken into account in the costs of the area outside the territory within the non‐unified solution, optimal moose population size will be higher for the outer area than under the unified solution. This results in an overall economic loss, which increases with increasing migration rates. Whenever the boundaries of political or management units do not follow those of ecological processes, ignoring the spatial resolution of the ecological process will result in sub‐optimal management of a renewable resource.

The impact of population size on the evolution of asexual microbes on smooth versus rugged fitness landscapes

BackgroundIt is commonly thought that large asexual populations evolve more rapidly than smaller ones, due to their increased rate of beneficial mutations. Less clear is how population size influences the level of fitness an asexual population can attain. Here, we simulate the evolution of bacteria in repeated serial passage experiments to explore how features such as fitness landscape ruggedness, the size of the mutational target under selection, and the mutation supply rate, interact to affect the evolution of microbial populations of different sizes.ResultsWe find that if the fitness landscape has many local peaks, there can be a trade-off between the rate of adaptation and the potential to reach high fitness peaks. This result derives from the fact that whereas large populations evolve mostly deterministically and often become trapped on local fitness peaks, smaller populations can follow more stochastic evolutionary paths and thus locate higher fitness peaks. We also find that the target size of adaptation and the mutation rate interact with population size to influence the trade-off between rate of adaptation and final fitness.ConclusionOur study suggests that the optimal population size for adaptation depends on the details of the environment and on the importance of either the ability to evolve rapidly or to reach high fitness levels.

Single-angle-of-incidence ellipsometry

We introduce single angle-of-incidence (SAI) ellipsometry [U.S. patent application 20070024850 (14 July 2006)] as a technique to completely identify, i.e., totally characterize, film-substrate systems. We show that only one measurement of the ellipsometric function rho at one angle of incidence and one wavelength is totally sufficient to determine the optical constant of the film N1, its thickness d, and the substrate's optical constant N2. Obviously, it is also sufficient for characterizing only the film, determining N1 and d, and for characterizing only the substrate, determining N2 and d, as well as for characterizing only bare substrates. An inverse genetic algorithm (IGA) for complete identification is presented that is based on a physical condition of the transparent-film-absorbing-substrate system . This IGA is used to identify the film-substrate system in four separate cases. We show that removing the film thickness from the fitness function of the genetic algorithm and using the defined optimum population size to characterize the film reduces the computational effort from 20,000 to 69 fitness-function calculations; the number of calculations to characterize an absorbing layer is reduced from 80,000 to 180. This is a very significant reduction and is very welcome in real-time applications. An error analysis is presented that shows that the IGA is resilient to, not affected by, random experimental errors and that it gives very good results in the presence of both random and systematic errors of the ellipsometer system. Experimental results are given that also prove the robustness, stability, and high accuracy of the method. We present data only for the SiO2-Si film-substrate system, but the IGA works for any film-substrate system, physical or not.

Optimal Population Size and Urban-Rural Composition of a Distant, Large, Arid Island: A Model and Some Numerical Simulations

Low population density and large distance from civilization centers generate high costs of isolation. Immigra- tion reduces these costs for veteran residents but reduces social and cultural cohesion, increases the demand for scarce re- sources and affects the rate of urban unemployment. An expected net benefit maximization model for determining the op- timal population size and the equilibrium urban-rural composition of an island similar to Australia is constructed. The model is simulated for various agricultural water prices. The simulation results illustrate the central role of the effect of immigration on urban unemployment rate in the determination of the island's optimal population size. INTRODUCTION This paper deals with the optimal population size and rural-urban composition of a distant, large, arid island. The island's current population is small and has a low fertility rate. Distance and dispersion hinder communication and provision of commodities and services and the island's in- habitants bear mental and material costs of isolation. Immi- gration is the main way for increasing the island's population density, strengthening the island's international integration and, thereby, moderating the costs of isolation borne by the island's inhabitants. However, immigration reduces the is- land's levels of cultural and social cohesion. It also affects the island's rural and urban land and water use and natural

Optimal Population Size and Urban-Rural Composition of a Distant, Large, Arid Island: A Model and Some Numerical Simulations

Optimal Population Size and Urban-Rural Composition of a Distant, Large, Arid Island: A Model and Some Numerical Simulations

Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)--also known as dissortative mating--, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA's mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.

Invasive Species Control over Space and Time:Miconia calvescenson Oahu, Hawaii

The optimal size and location of an invasive species population depend upon spatially differentiated biological growth, economic costs, and damages. Although largely absent from most economic models, spatial considerations matter because the likelihood and magnitude of the invasion vary spatially and the threatened assets may be unevenly distributed across space. We map the current and future populations of an invasive species,Miconia calvescens,on Oahu, Hawaii, and the potential damages to water quantity, quality, and endangered-species habitat, and weigh these against treatment costs. We find that optimal densities vary from approximately 1% to 18% cover throughout the island.

Comparison of Phenotype and Combined Index Selection at Optimal Breeding Population Size Considering Gain and Gene Diversity

Abstract A breeding program was simulated in this study. Two alternative ways of selecting the breeding population for the following generation was compared. Phenotypic selection, which means to select just on the individual performance, and combined index selection, which means selection on predicted breeding value for each individual obtained by weighting family average and individual phenotype, were compared. The plant number (testing resource) and gene diversity (status number, Ns) were kept constant, but the breeding population size was variable and chosen for maximizing gain for the particular breeding scenario. At low and medium heritability phenotypic selection was inferior to combined index selection. Only when heritability was high phenotypic selection was as efficient (generation 1) as or more efficient (generation 5) than combined index selection. This contrasts to earlier studies done under constant breeding population size, where selection methods appeared similar. The advantage in gain of combined index selection is usually at a larger breeding population size. At limited heritability and breeding population size the difference is considerable. When breeding population size was kept rather small (<100), and the heritability limited, combined index selection can result in slightly higher gain than phenotypic selection at the same gene diversity, but this was at the cost of a much larger breeding population. Phenotypic selection and combined index selection appears as rather similar for many cases in this simple model used in this study. Considering other advantages with phenotypic selection, it may often be regarded as a competitive alternative.

Optimal control of Atlantic population Canada geese

Management of Canada geese ( Branta canadensis) can be a balance between providing sustained harvest opportunity while not allowing populations to become overabundant and cause damage. In this paper, we focus on the Atlantic population of Canada geese and use stochastic dynamic programming to determine the optimal harvest strategy over a range of plausible models for population dynamics. There is evidence to suggest that the population exhibits significant age structure, and it is possible to reconstruct age structure from surveys. Consequently the harvest strategy is a function of the age composition, as well as the abundance, of the population. The objective is to maximize harvest while maintaining the number of breeding adults in the population between specified upper and lower limits. In addition, the total harvest capacity is limited and there is uncertainty about the strength of density-dependence. We find that under a density-independent model, harvest is maximized by maintaining the breeding population at the highest acceptable abundance. However if harvest capacity is limited, then the optimal long-term breeding population size is lower than the highest acceptable level, to reduce the risk of the population growing to an unacceptably large size. Under the proposed density-dependent model, harvest is maximized by maintaining the breeding population at an intermediate level between the bounds on acceptable population size; limits to harvest capacity have little effect on the optimal long-term population size. It is clear that the strength of density-dependence and constraints on harvest significantly affect the optimal harvest strategy for this population. Model discrimination might be achieved in the long term, while continuing to meet management goals, by adopting an adaptive management strategy.

Cumulative effects of multiple sources of bias in estimating spawner–recruit parameters with application to harvested stocks of Chinook salmon ( Oncorhynchus tshawytscha)

Previous studies of bias in estimating spawner–recruit relationships have usually focused on a single source of bias, and have typically found bias that tends to overestimate productivity and underestimate optimal population size. However, many of these studies have used simulated data contrived to maximize the bias. This study examined the cumulative effects of multiple sources of bias using simulations with life history parameters based on Chinook salmon ( Oncorhynchus tshawytscha) stocks used as escapement indicator stocks for management of ocean salmon fisheries. Sources of bias incorporated in the simulations include time series bias, observational errors, and errors in estimating age composition. Cumulative biases in parameter estimates were found to be relatively small in most cases, and the resulting management reference points tended to err in the direction of conservation rather than in the direction of overexploitation. However, the same methods applied to depleted stocks would result in substantial bias that would tend to contribute to overexploitation.

Group size of feeding stream case-bearing caddisfly grazers and resource abundance

Summary Several herbivorous insects are known to benefit from feeding in groups; however, little is known about (1) the resource conditions under which herbivorous insects perform group feeding and (2) the optimum population size to get any benefits by group feeding, for example, in terms of growth performance. To test the hypotheses that the benefits from group feeding change with resource level and population size, we performed field investigations and an enclosure experiment using the grazer caddisfly larva Micrasema quadriloba . The field investigations revealed aggregated distributions of larvae (indicator of aggregation, I δ =4.1±1.55, aggregated density: 12.7±5.3 individuals per 3.1×3.1 cm 2 (mean±1 SD)) when periphyton was abundant on stream cobbles and random distributions ( I δ =1.0±0.11) when periphyton was scarce. In the enclosure experiment, the relative growth rate (RGR) of the larvae at each population size showed different tendencies at high and low periphyton abundance levels; RGR with abundant periphyton had a convex curve with a peak at intermediate population size, whereas RGR with scarce periphyton decreased linearly with increasing population size. The benefits from group feeding thus changed with resource level; larvae obtained high growth performance by group feeding behavior only when the resource was sufficiently abundant. The present study revealed not only that the optimum group size of larvae increased their growth performance, but also that this optimum group size occurred frequently in the field. We also discuss the mechanisms and benefits of group feeding by case-bearing caddisfly grazers.

The Emergence and Performance of Indigenous Peoples’ Parties in South America

One of the most significant and unexpected developments in Latin America during the past 10 years is the emergence of parties organized around indigenous identity. The authors use subnational data from six South American countries (Bolivia, Chile, Colombia, Ecuador, Peru, and Venezuela) to examine the factors responsible for the variation in the emergence and performance of indigenous peoples’ political parties in the region. Using a pooled cross-sectional twin snapshot analysis, the authors find that although indigenous party formation is the result of favorable institutional, demographic, and political conditions, such as permissive electoral rules, optimal indigenous population size, and a regional diffusion effect with respect to indigenous activism, enhanced electoral performance of these parties is determined by structural and political conditions, including higher rates of poverty and less salient class-based identities, in addition to the favorable conditions mentioned above.