Fitness, inclusive fitness, and optimization

Individual-as-maximizing agent analogies result in a simple understanding of the functioning of the biological world. Identifying the conditions under which individuals can be regarded as fitness maximizing agents is thus of considerable interest to biologists. Here, we compare different concepts of fitness maximization, and discuss within a single framework the relationship between Hamilton's (J Theor Biol 7: 1-16, 1964) model of social interactions, Grafen's (J Evol Biol 20: 1243-1254, 2007a) formal Darwinism project, and the idea of evolutionary stable strategies. We distinguish cases where phenotypic effects are additive separable or not, the latter not being covered by Grafen's analysis. In both cases it is possible to define a maximand, in the form of an objective function phi(z), whose argument is the phenotype of an individual and whose derivative is proportional to Hamilton's inclusive fitness effect. However, this maximand can be identified with the expression for fecundity or fitness only in the case of additive separable phenotypic effects, making individual-as-maximizing agent analogies unattractive (although formally correct) under general situations of social interactions. We also feel that there is an inconsistency in Grafen's characterization of the solution of his maximization program by use of inclusive fitness arguments. His results are in conflict with those on evolutionary stable strategies obtained by applying inclusive fitness theory, and can be repaired only by changing the definition of the problem.

Bayesian nash equilibrium in ''linear'' cournot models with private information about costs

Calculating explicit closed form solutions of Cournot models where firms have private information about their costs is, in general, very cumbersome. Most authors consider therefore linear demands and constant marginal costs. However, within this framework, the nonnegativity constraint on prices (and quantities) has been ignored or not properly dealt with and the correct calculation of all Bayesian Nash equilibria is more complicated than expected. Moreover, multiple symmetric and interior Bayesianf equilibria may exist for an open set of parameters. The reason for this is that linear demand is not really linear, since there is a kink at zero price: the general ''linear'' inverse demand function is P (Q) = max{a - bQ, 0} rather than P (Q) = a - bQ.

Algorithm creation and optimization for the crew pairing problem

Algoritmo que optimiza y crea pairings para tripulaciones de líneas aéreas mediante la posterior programación en Java.

Optimization of floor cleaning coverage performance of a random path-planning mobile robot

Floor cleaning is a typical robot application. There are several mobile robots aviable in the market for domestic applications most of them with random path-planning algorithms. In this paper we study the cleaning coverage performances of a random path-planning mobile robot and propose an optimized control algorithm, some methods to estimate the are of the room, the evolution of the cleaning and the time needed for complete coverage.

Genetic structure of a linear population of Beta vulgaris ssp maritima (sea beet) revealed by isozyme and RFLP analysis

Knowledge of the genetic structure of plant populations is necessary for the understanding of the dynamics of major ecological processes. It also has applications in conservation biology and risk assessment for genetically modified crops. This paper reports the genetic structure of a linear population of sea beet, Beta vulgaris ssp. maritima (the wild relative of sugar beet), on Furzey Island, Poole Harbour. The relative spatial positions of the plants were accurately mapped and the plants were scored for variation at isozyme and RFLP loci. Structure was analysed by repeated subdivision of the population to find the average size of a randomly mating group. Estimates of F-ST between randomly mating units were then made, and gave patterns consistent with the structure of the population being determined largely by founder effects. The implications of these results for the monitoring of transgene spread in wild sea beet populations are discussed.

A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.

Algorithm optimization for solving crew scheduling problems

In this paper, we are proposing a methodology to determine the most efficient and least costly way of crew pairing optimization. We are developing a methodology based on algorithm optimization on Eclipse opensource IDE using the Java programming language to solve the crew scheduling problems.

An Analysis of black-box optimization problems in reinsurance: evolutionary-based approaches

Black-box optimization problems (BBOP) are de ned as those optimization problems in which the objective function does not have an algebraic expression, but it is the output of a system (usually a computer program). This paper is focussed on BBOPs that arise in the eld of insurance, and more speci cally in reinsurance problems. In this area, the complexity of the models and assumptions considered to de ne the reinsurance rules and conditions produces hard black-box optimization problems, that must be solved in order to obtain the optimal output of the reinsurance. The application of traditional optimization approaches is not possible in BBOP, so new computational paradigms must be applied to solve these problems. In this paper we show the performance of two evolutionary-based techniques (Evolutionary Programming and Particle Swarm Optimization). We provide an analysis in three BBOP in reinsurance, where the evolutionary-based approaches exhibit an excellent behaviour, nding the optimal solution within a fraction of the computational cost used by inspection or enumeration methods.

Linear response functions for a vibrational configuration interaction state

Linear response functions are implemented for a vibrational configuration interaction state allowing accurate analytical calculations of pure vibrational contributions to dynamical polarizabilities. Sample calculations are presented for the pure vibrational contributions to the polarizabilities of water and formaldehyde. We discuss the convergence of the results with respect to various details of the vibrational wave function description as well as the potential and property surfaces. We also analyze the frequency dependence of the linear response function and the effect of accounting phenomenologically for the finite lifetime of the excited vibrational states. Finally, we compare the analytical response approach to a sum-over-states approach

Variational calculation of vibrational linear and nonlinear optical properties

A variational approach for reliably calculating vibrational linear and nonlinear optical properties of molecules with large electrical and/or mechanical anharmonicity is introduced. This approach utilizes a self-consistent solution of the vibrational Schrödinger equation for the complete field-dependent potential-energy surface and, then, adds higher-level vibrational correlation corrections as desired. An initial application is made to static properties for three molecules of widely varying anharmonicity using the lowest-level vibrational correlation treatment (i.e., vibrational Møller-Plesset perturbation theory). Our results indicate when the conventional Bishop-Kirtman perturbation method can be expected to break down and when high-level vibrational correlation methods are likely to be required. Future improvements and extensions are discussed

Assembling genes from predicted exons in linear time with dynamic programming

In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.

Dose optimization approach to fast X-ray microtomography of the lung alveoli.

A basic prerequisite for in vivo X-ray imaging of the lung is the exact determination of radiation dose. Achieving resolutions of the order of micrometres may become particularly challenging owing to increased dose, which in the worst case can be lethal for the imaged animal model. A framework for linking image quality to radiation dose in order to optimize experimental parameters with respect to dose reduction is presented. The approach may find application for current and future in vivo studies to facilitate proper experiment planning and radiation risk assessment on the one hand and exploit imaging capabilities on the other.

Dowel Bar Optimization: Phases I and II, October 2001

America’s roadways are in serious need of repair. According to the American Society of Civil Engineers (ASCE), one-third of the nation’s roads are in poor or mediocre condition. ASCE has estimated that under these circumstances American drivers will sacrifice $5.8 billion and as many as 13,800 fatalities a year from 1999 to 2001 ( 1). A large factor in the deterioration of these roads is a result of how well the steel reinforcement transfers loads across the concrete slabs. Fabricating this reinforcement using a shape conducive to transferring these loads will help to aid in minimizing roadway damage. Load transfer within a series of concrete slabs takes place across the joints. For a typical concrete paved road, these joints are approximately 1/8-inch gaps between two adjacent slabs. Dowel bars are located at these joints and used to transfer load from one slab to its adjacent slabs. As long as the dowel bar is completely surrounded by concrete no problems will occur. However, when the hole starts to oblong a void space is created and difficulties can arise. This void space is formed due to a stress concentration where the dowel contacts the concrete. Over time, the repeated process of traffic traveling over the joint crushes the concrete surrounding the dowel bar and causes a void in the concrete. This void inhibits the dowel’s ability to effectively transfer load across the joint. Furthermore, this void gives water and other particles a place to collect that will eventually corrode and potentially bind or lock the joint so that no thermal expansion is allowed. Once there is no longer load transferred across the joint, the load is transferred to the foundation and differential settlement of the adjacent slabs will occur.