Ocotlán Díaz-Parra

Similarities between meta-heuristics algorithms and the science of life

In this paper, we show the functional similarities between Meta-heuristics and the aspects of the science of life (biology): (a) Meta-heuristics based on gene transfer: Genetic algorithms (natural evolution of genes in an organic population), Transgenic Algorithm (transfers of genetic material to another cell that is not descending); (b) Meta-heuristics based on interactions among individual insects: Ant Colony Optimization (on interactions among individuals insects, Ant Colonies), Firefly algorithm (fireflies of the family Lampyridze), Marriage in honey bees Optimization algorithm (the process of reproduction of Honey Bees), Artificial Bee Colony algorithm (the process of recollection of Honey Bees); and (c) Meta-heuristics based on biological aspects of alive beings: Tabu Search Algorithm (Classical Conditioning on alive beings), Simulated Annealing algorithm (temperature control of spiders), Particle Swarm Optimization algorithm (social behavior and movement dynamics of birds and fish) and Artificial Immune System (immunological mechanism of the vertebrates).

Survey of polynomial transformations between NP-complete problems

This paper aims at being a guide to understand polynomial transformations and polynomial reductions between NP-complete problems by presenting the methodologies for polynomial reductions/transformations and the differences between reductions and transformations. To this end the article shows examples of polynomial reductions/transformations and the restrictions to reduce/transform between NP-complete problems. Finally, this paper includes a digraph with the historical reductions/transformations between instances of NP-complete problems and introduces the term family of polynomial transformations.

Applied Statistical Indicators to the Vehicle Routing Problem with Time Windows for Discriminate Appropriately the Best Algorithm

In this paper, we propose indicators based on the position method of the descriptive statistic for the Vehicle Routing Problem with Time Windows (VRPTW). The indicators are based on the calculation of the median; they will serve altogether with the technique of discriminant analysis to select appropriately the algorithm that better solves an instance of the VRPTW.

A Metric to Discriminate the Selection of Algorithms for the General ATSP Problem

In this paper we propose: (1) the use of discriminant analysis as a means for predictive learning (data-mining techniques) aiming at selecting metaheuristic algorithms and (2) the use of a metric for improving the selection of the algorithms that best solve a given instance of the Asymmetric Traveling Salesman Problem (ATSP). The only metric that had existed so far to determine the best algorithm for solving an ATSP instance is based on the number of cities; nevertheless, it is not sufficiently adequate for discriminating the best algorithm for solving an ATSP instance, thus the necessity for devising a new metric through the use of data-mining techniques.

Selection of an investment portfolio by means of multi-objective mathematical model applied to mexican stock market in period of debacle

The selection of a portfolio of investment through a multi-objective mathematical model indicates that it possible have several available portfolios. In our model, the selection of one of them is performed with the same principle used by the Capital Assets Pricing Model, a single point touches the border of optimal portfolios. The model is tested with selection of an investment portfolio during period debacle of the Mexican Stock Market. This is possible because our model can be applied when there is no positive return. The results show that it is possible to obtain profit positive investment portfolios in periods of debacle.