A tensor analysis improved genetic algorithm for online bin packing

Mutation in a Genetic Algorithm is the key variation operator adjusting the genetic diversity in a population throughout the evolutionary process. Often, a fixed mutation probability is used to perturb the value of a gene. In this study, we describe a novel data science approach to adaptively generate the mutation probability for each locus. The trail of high quality candidate solutions obtained during the search process is represented as a 3rd order tensor. Factorizing that tensor captures the common pattern between those solutions, identifying the degree of mutation which is likely to yield improvement at each locus. An online bin packing problem is used as an initial case study to investigate the proposed approach for generating locus dependent mutation probabilities. The empirical results show that the tensor approach improves the performance of a standard Genetic Algorithm on almost all classes of instances, significantly

Unified Solution of the Expected Maximum of a Random Walk and the Discrete Flux to a Spherical Trap

Two random-walk related problems which have been studied independently in the past, the expected maximum of a random walker in one dimension and the flux to a spherical trap of particles undergoing discrete jumps in three dimensions, are shown to be closely related to each other and are studied using a unified approach as a solution to a Wiener-Hopf problem. For the flux problem, this work shows that a constant c = 0.29795219 which appeared in the context of the boundary extrapolation length, and was previously found only numerically, can be derived explicitly. The same constant enters in higher-order corrections to the expected-maximum asymptotics. As a byproduct, we also prove a new universal result in the context of the flux problem which is an analogue of the Sparre Andersen theorem proved in the context of the random walker's maximum.Comment: Two figs. Accepted for publication, Journal of Statistical Physic

Un nuevo enfoque para el mejoramiento de arroz en América Latina

La crisis ocasionada por la deuda externa ha debilitado los programas nacionales de investigación de arroz en América Latina, y ha aumentado su dependencia de los programas regionales y mundiales del CIAT y del IRRI.Si bien el germoplasma mejorado producido por los IARC ha traído consigo cierto grado de uniformidad genética, también ha brindado inmensos beneficios a los programas nacionales de investigación agrícola y a los productores de arroz de la región. Estos beneficios se ven hoy en día amenazados, ya que tanto el IRRI como el CIAT, en respuesta a las presiones ejercidas por sus donantes, han comenzado a "avanzar" hacia la biotecnología, y están tratando de extrapolar el éxito que han tenido en sus programas de mejoramiento de cultivos a la compleja labor del manejo de los recursos. Una nueva estrategia para el mejoramiento del arroz en América Latina debe tener en cuenta los puntos siguientes: 1) desde el punto de vista de la diversidad genética, es conveniente abandonar el método de mejoramiento centralizado empleado por el IRRI y el CIAT; 2) el CIAT reducirá los recursos destinados al mejoramiento convencional del arroz, yse ocupará más de las biotecnologías que apoyen el mejoramiento del arroz; y 3) un plan factible (con posibilidades de éxito) debe utilizar, de manera más eficaz, los recursos humanos de los programas nacionales de investigación que hoy languidecen a causa de las restricciones económicas. Una estrategia semejante debe incluir: 1) la identificación y el establecimiento de sitios experimentales esenciales para el mejoramiento; 2) la evolución de INGER hacia una entidad cooperativa de contratación; y 3) el CIAT considerado como fuente de tecnología avanzada

Ant colony optimisation and local search for bin-packing and cutting stock problems

The Bin Packing Problem and the Cutting Stock Problem are two related classes of NP-hard combinatorial optimization problems. Exact solution methods can only be used for very small instances, so for real-world problems, we have to rely on heuristic methods. In recent years, researchers have started to apply evolutionary approaches to these problems, including Genetic Algorithms and Evolutionary Programming. In the work presented here, we used an ant colony optimization (ACO) approach to solve both Bin Packing and Cutting Stock Problems. We present a pure ACO approach, as well as an ACO approach augmented with a simple but very effective local search algorithm. It is shown that the pure ACO approach can compete with existing evolutionary methods, whereas the hybrid approach can outperform the best-known hybrid evolutionary solution methods for certain problem classes. The hybrid ACO approach is also shown to require different parameter values from the pure ACO approach and to give a more robust performance across different problems with a single set of parameter values. The local search algorithm is also run with random restarts and shown to perform significantly worse than when combined with ACO

The evolution of Runx genes I. A comparative study of sequences from phylogenetically diverse model organisms

BACKGROUND: Runx genes encode proteins defined by the highly conserved Runt DNA-binding domain. Studies of Runx genes and proteins in model organisms indicate that they are key transcriptional regulators of animal development. However, little is known about Runx gene evolution. RESULTS: A phylogenetically broad sampling of publicly available Runx gene sequences was collected. In addition to the published sequences from mouse, sea urchin, Drosophila melanogaster and Caenorhabditis elegans, we collected several previously uncharacterised Runx sequences from public genome sequence databases. Among deuterostomes, mouse and pufferfish each contain three Runx genes, while the tunicate Ciona intestinalis and the sea urchin Strongylocentrotus purpuratus were each found to have only one Runx gene. Among protostomes, C. elegans has a single Runx gene, while Anopheles gambiae has three and D. melanogaster has four, including two genes that have not been previously described. Comparative sequence analysis reveals two highly conserved introns, one within and one just downstream of the Runt domain. All vertebrate Runx genes utilize two alternative promoters. CONCLUSIONS: In the current public sequence database, the Runt domain is found only in bilaterians, suggesting that it may be a metazoan invention. Bilaterians appear to ancestrally contain a single Runx gene, suggesting that the multiple Runx genes in vertebrates and insects arose by independent duplication events within those respective lineages. At least two introns were present in the primordial bilaterian Runx gene. Alternative promoter usage arose prior to the duplication events that gave rise to three Runx genes in vertebrates

General flux to a trap in one and three dimensions

The problem of the flux to a spherical trap in one and three dimensions, for diffusing particles undergoing discrete-time jumps with a given radial probability distribution, is solved in general, verifying the Smoluchowski-like solution in which the effective trap radius is reduced by an amount proportional to the jump length. This reduction in the effective trap radius corresponds to the Milne extrapolation length.Comment: Accepted for publication, in pres

Three-qubit pure-state canonical forms

In this paper we analyze the canonical forms into which any pure three-qubit state can be cast. The minimal forms, i.e. the ones with the minimal number of product states built from local bases, are also presented and lead to a complete classification of pure three-qubit states. This classification is related to the values of the polynomial invariants under local unitary transformations by a one-to-one correspondence.Comment: REVTEX, 9 pages, 1 figur

Properties of Entanglement Monotones for Three-Qubit Pure States

Various parameterizations for the orbits under local unitary transformations of three-qubit pure states are analyzed. The interconvertibility, symmetry properties, parameter ranges, calculability and behavior under measurement are looked at. It is shown that the entanglement monotones of any multipartite pure state uniquely determine the orbit of that state under local unitary transformations. It follows that there must be an entanglement monotone for three-qubit pure states which depends on the Kempe invariant defined in [Phys. Rev. A 60, 910 (1999)]. A form for such an entanglement monotone is proposed. A theorem is proved that significantly reduces the number of entanglement monotones that must be looked at to find the maximal probability of transforming one multipartite state to another.Comment: 14 pages, REVTe