Evolutionary Optimality of Delayed Breeding in voles

Oikos ◽  
1996 ◽  
Vol 77 (1) ◽  
pp. 173 ◽  
Author(s):  
Hanna Kokko ◽  
Esa Ranta
Keyword(s):  
Evolutionary Optimality

scholarly journals Eco‐evolutionary optimality as a means to improve vegetation and land‐surface models

2021 ◽  
Author(s):  
Sandy P. Harrison ◽  
Wolfgang Cramer ◽  
Oskar Franklin ◽  
Iain Colin Prentice ◽  
Han Wang ◽  
...  
Keyword(s):  
Land Surface ◽  
Land Surface Models ◽  
Surface Models ◽  
Evolutionary Optimality

Stability indicatrices of nonnegative matrices and some of their applications in problems of biology and epidemiology

2019 ◽  
Vol 34 (5) ◽  
pp. 269-275
Author(s):  
Valery N. Razzhevaikin
Keyword(s):  
Nonnegative Matrix ◽  
Host Population ◽  
Nonnegative Matrices ◽  
Biological Communities ◽  
Evolutionary Selection ◽  
Evolutionary Optimality ◽  
Selection For ◽  
The Stability ◽  
Series Of Functions

Abstract The method of constructing a stability indicatrix of a nonnegative matrix having the form of a polynomial of its coefficients is presented. The algorithm of construction and conditions of its applicability are specified. The applicability of the algorithm is illustrated on examples of constructing the stability indicatrix for a series of functions widely used in simulation of the dynamics of discrete biological communities, for solving evolutionary optimality problems arising in biological problems of evolutionary selection, for identification of the conditions of the pandemic in a distributed host population.

scholarly journals EVOLUTIONARY OPTIMALITY APPLIED TO DROSOPHILA EXPERIMENTS: HYPOTHESIS OF CONSTRAINED REPRODUCTIVE EFFICIENCY

Evolution ◽  
2002 ◽  
Vol 56 (6) ◽  
pp. 1136-1149 ◽  
Author(s):  
V. N. Novoseltsev ◽  
R. Arking ◽  
J. A. Novoseltseva ◽  
A. I. Yashin
Keyword(s):  
Reproductive Efficiency ◽  
Evolutionary Optimality

scholarly journals Evolutionary optimality in stochastic search problems

2010 ◽  
Vol 7 (50) ◽  
pp. 1301-1310 ◽  
Author(s):  
Mark D. Preston ◽  
Jonathan W. Pitchford ◽  
A. Jamie Wood
Keyword(s):  
Computational Models ◽  
Heavy Tails ◽  
Fitness Function ◽  
Population Level ◽  
Stochastic Search ◽  
Environmental Stochasticity ◽  
Encounter Rate ◽  
Search Problems ◽  
Lévy Walks ◽  
Evolutionary Optimality

‘Optimal’ behaviour in a biological system is not simply that which maximizes a mean, or temporally and spatially averaged, fitness function. Rather, population dynamics and demographic and environmental stochasticity are fundamental evolutionary ingredients. Here, we revisit the problem of optimal foraging, where some recent studies claim that organisms should forage according to Lévy walks. We show that, in an ecological scenario dominated by uncertainty and high mortality, Lévy walks can indeed be evolutionarily favourable. However, this conclusion is dependent on the definition of efficiency and the details of the simulations. We analyse measures of efficiency that incorporate population-level characteristics, such as variance, superdiffusivity and heavy tails, and compare the results with those generated by simple maximizing of the average encounter rate. These results have implications on stochastic search problems in general, and also on computational models of evolutionary optima.

EVOLUTIONARY OPTIMALITY APPLIED TO DROSOPHILA EXPERIMENTS: HYPOTHESIS OF CONSTRAINED REPRODUCTIVE EFFICIENCY

Evolution ◽  
2002 ◽  
Vol 56 (6) ◽  
pp. 1136 ◽  
Author(s):  
V. N. Novoseltsev ◽  
R. Arking ◽  
J. A. Novoseltseva ◽  
A. I. Yashin
Keyword(s):  
Reproductive Efficiency ◽  
Evolutionary Optimality

scholarly journals Computational Exploration of the Biological Basis of Black-Scholes Expected Utility Function

2007 ◽  
Vol 2007 ◽  
pp. 1-15 ◽  
Author(s):  
Sukanto Bhattacharya ◽  
Kuldeep Kumar
Keyword(s):  
Genetic Algorithm ◽  
Utility Function ◽  
Expected Utility ◽  
Functional Form ◽  
Biological Basis ◽  
Black Scholes ◽  
Computational Exploration ◽  
Evolutionary Optimality ◽  
Successive Generations ◽  
Genetic Algorithm Model

It has often been argued that there exists an underlying biological basis of utility functions. Taking this line of argument a step further in this paper, we have aimed to computationally demonstrate the biological basis of the Black-Scholes functional form as applied to classical option pricing and hedging theory. The evolutionary optimality of the classical Black-Scholes function has been computationally established by means of a haploid genetic algorithm model. The objective was to minimize the dynamic hedging error for a portfolio of assets that is built to replicate the payoff from a European multi-asset option. The functional form that is seen to evolve over successive generations which best attains this optimization objective is the classical Black-Scholes function extended to a multiasset scenario.Computational Exploration of the Biological Basis of Black-Scholes Expected Utility Function

scholarly journals Evolutionary optimality in sex differences of longevity and athletic performances

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Hiromi Asanuma ◽  
Satoshi Kakishima ◽  
Hiromu Ito ◽  
Kazuya Kobayashi ◽  
Eisuke Hasegawa ◽  
...  
Keyword(s):  
Sex Differences ◽  
Evolutionary Optimality
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