Jorge A. Ruiz-Vanoye

A Survey of Transportation Problems

This paper aims at being a guide to understand the different types of transportation problems by presenting a survey of mathematical models and algorithms used to solve different types of transportation modes (ship, plane, train, bus, truck, Motorcycle, Cars, and others) by air, water, space, cables, tubes, and road. Some problems are as follows: bus scheduling problem, delivery problem, combining truck trip problem, open vehicle routing problem, helicopter routing problem, truck loading problem, truck dispatching problem, truck routing problem, truck transportation problem, vehicle routing problem and variants, convoy routing problem, railroad blocking problem (RBP), inventory routing problem (IRP), air traffic flow management problem (TFMP), cash transportation vehicle routing problem, and so forth.

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).

A vertical transfer algorithm for the School Bus Routing Problem

In this paper is a solution to the School Bus Routing Problem by the application of a bio-inspired algorithm in the vertical transfer of genetic material to offspring or the inheritance of genes by subsequent generations. The vertical transfer algorithm or Genetic algorithm uses the clusterization population pre-selection operator, tournament selection, crossover-k operator and an intelligent mutation operator called mutation-S. The use of the bio-inspired algorithm to solve SBRP instances show good results about Total Bus Travel Distance and the Number of Buses with the Routes.

Selection of an Investment Portfolio by Means of a Mathematical Model of Optimization Applied to Mexican Stock-Market in Period of Debacle

In this paper appears a behavior analysis of the Mexican stock-market between a previous period to the economic debacle of the 2008 and during the period of the first month of the debacle. We propose to use a mathematical model of linear programming for the selection of an investment portfolio in Mexican stock-market. The mathematical model is based on the modification of Markowitz Model and Capital Assets Pricing Model. The model proposed contains two functions objective: 1) to maximize the return and 2) to minimize the risk. The Application of the proposed model to select an investment portfolio was realized with the public data of Mexican stock-market taking a sample from the stock-exchange, than they are part of the calculation of the Index of Prices and Quotations. The results show that our model is able to determine an investment portfolio with very different scenes and in period of debacle. Also it does determine that when comparing two investment portfolios are better to select the portfolio with the greater return instead of the portfolio with the smaller risk.

A transgenic algorithm for the Vehicle Routing Problem with Time Windows

In this paper, we present a transgenic computer algorithm based on the transformation mechanism of horizontal gene transfer to solve the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW is the problem of minimising transportation costs while satisfying some restrictions as the time, vehicle capacity and the demand of each client. Horizontal gene artificial transfer is a form of genetic engineering. The transgenic algorithm is considered as a horizontal gene transfer algorithm, a meta-heuristics algorithm, or a bio-inspired algorithm based on horizontal gene transfer and symbiogenesis. The transgenic algorithm uses a data-mining technique (clustering) to group similar characteristics of the VRPTW instance to obtain the initial population (one VRPTW individual), a genetic transfer phase inspired by the transference of genetic codes of a bacterial gene (depot) contained in mechanisms for the horizontal gene transfer, and an intelligent mutation operator inspired by symbiogenesis called symbion operator. The transgenic algorithm (lateral gene transfer algorithm, or horizontal gene transfer algorithm) involves deliberate genetic modification rather than evolutionary aspects. We demonstrate that it is possible to deploy a transgenic algorithm based on horizontal gene transfer to solve (in fewer generations and less time) the VRPTW than the results of the genetic algorithm.

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.

An Alternative Solution Initiative to Problematic of Computer Science Security of Virus and Malware with Experimentation of Firewalls and Antivirus

Exist in the computer science market a great amount of antivirus, the election of one of them depends on the company. But truly they are necessary, or with a tool we can be protected of the virus and the accesses no authorized our computer. In this document one sets out to demonstrate that firewall personal formed good will protect to us of the intruders and the virus.

A Solution to the Strongly Correlated 0-1 Knapsack Problem by a Binary Branch and Bound Algorithm

In this paper is presented the Binary Branch-and-Bound Algorithm (BBBA) and its application to determine the solution of the 0-1 Knapsack Problem. The algorithm solves different instances (uncorrelated, weakly and strongly correlated) in time (Kn). The proposed algorithm was experimentally compared with the Pisinger Model, based on the obtained results it is demonstrated the ability of the proposed algorithm to solve problems that the Pisinger algorithm cannot solve.

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.

Surveying the Optimization Problems of Water Distribution Networks

This paper aims to guide understanding of the different types of optimization problems of water distribution networks by presenting a survey of mathematical models and algorithms used to solve the variants of said networks. Problems include water resource planning, water quality management, water supply networks, water distribution systems, water flow and chemical transport, and water distribution network. Optimizing resources to transport water is an issue of global interest and is important to minimize the costs of construction of pipeline to supply water, repair costs, and water transportation.