THE EVALUATION OF ENTERPRISE APPLICATION INTEGRATION APPROACHES TO RESOLVE POSTAL PARCEL DELIVERY TRANSPORT ROUTING PROBLEMS

Information Technologies (IT) create interconnected application software. Nowadays, one of the vital problems is the enterprise application software integration. Systems of the transport routing become more complicated, because in order to efficiently solve transport routing and planning problems, it is necessary to get more and more information. Enterprise application methods and technologies allow to create effective transport routing system. To structure integration solutions, can be used different options and solutions, as well as platform of integration, but vital problem is the choice of the most suitable integration approach. The aim of this paper is to evaluate several accessible integration solutions. Integration options are identified and classified according to integration approach and technologies used in this paper. In practical assessment of integration technologies, post parcel delivery and routing process is used as an example, for which it is necessary to create effective GPS/GIS/ERP integration solution. For this problem, several alternative solutions have been developed. They have been evaluated according to their high-speed, easily of development and modification, as well as other parameters

A Neuro-Evolutionary Corpus-Based Method for Word Sense Disambiguation

International audienceWe propose a supervised approach to Word Sense Disambiguation based on Neural Networks combined with Evolutionary Algorithms. An established method to automatically design the structure and learn the connection weights of Neural Networks by means of an Evolutionary Algorithm is used to evolve a neural-network disambiguator for each polysemous word, against a dataset extracted from an annotated corpus. Two distributed encoding schemes, based on the orthography of words and characterized by different degrees of information compression, have been used to represent the context in which a word occurs. The performance of such encoding schemes has been compared. The viability of the approach has been demonstrated through experiments carried out on a representative set of polysemous words. Comparison with the best entry of the Semeval-2007 competition has shown that the proposed approach is almost competitive with state-of-the-art WSD approaches

Metaheurísticas aplicadas a problemas de optimización

El objetivo principal de esta línea de investigación es el diseño y desarrollo de algoritmos heurísticos y meta-heurísticos que resuelvan problemas de optimización. En particular se abordan problemas de corte y empaquetado, de ruteo de vehículos y de ensamblado de fragmentos de ADN. Actualmente dos de las ramas con más éxito para diseñar metaheurísticas eficientes, y dar solución a estos problemas, son la hibridación y el paralelismo. El trabajo está orientado a aplicar metaheurísticas secuenciales y paralelas a los problemas propuestos, a analizar los resultados para comprender el comportamiento de estos algoritmos y a proponer nuevos métodos para resolver los problemas de una manera más eficaz y eficiente.Eje: Agentes y sistemas inteligentesRed de Universidades con Carreras en Informática (RedUNCI

Metaheurísticas aplicadas a problemas de optimización

El objetivo principal de esta línea de investigación es el diseño y desarrollo de algoritmos heurísticos y meta-heurísticos que resuelvan problemas de optimización. En particular se abordan problemas de corte y empaquetado, de ruteo de vehículos y de ensamblado de fragmentos de ADN. Actualmente dos de las ramas con más éxito para diseñar metaheurísticas eficientes, y dar solución a estos problemas, son la hibridación y el paralelismo. El trabajo está orientado a aplicar metaheurísticas secuenciales y paralelas a los problemas propuestos, a analizar los resultados para comprender el comportamiento de estos algoritmos y a proponer nuevos métodos para resolver los problemas de una manera más eficaz y eficiente.Eje: Agentes y sistemas inteligentesRed de Universidades con Carreras en Informática (RedUNCI

Quantum annealing for vehicle routing and scheduling problems

Metaheuristic approaches to solving combinatorial optimization problems have many attractions. They sidestep the issue of combinatorial explosion; they return good results; they are often conceptually simple and straight forward to implement. There are also shortcomings. Optimal solutions are not guaranteed; choosing the metaheuristic which best fits a problem is a matter of experimentation; and conceptual differences between metaheuristics make absolute comparisons of performance difficult. There is also the difficulty of configuration of the algorithm - the process of identifying precise values for the parameters which control the optimization process. Quantum annealing is a metaheuristic which is the quantum counterpart of the well known classical Simulated Annealing algorithm for combinatorial optimization problems. This research investigates the application of quantum annealing to the Vehicle Routing Problem, a difficult problem of practical significance within industries such as logistics and workforce scheduling. The work devises spin encoding schemes for routing and scheduling problem domains, enabling an effective quantum annealing algorithm which locates new solutions to widely used benchmarks. The performance of the metaheuristic is further improved by the development of an enhanced tuning approach using fitness clouds as behaviour models. The algorithm is shown to be further enhanced by taking advantage of multiprocessor environments, using threading techniques to parallelize the optimization workload. The work also shows quantum annealing applied successfully in an industrial setting to generate solutions to complex scheduling problems, results which created extra savings over an incumbent optimization technique. Components of the intellectual property rendered in this latter effort went on to secure a patent-protected status

Algoritmos celulares con operadores específicos para resolver un problema de ruteo de vehículos

El Problema de Ruteo de Vehículos con Capacidad limitada consiste en encontrar la mejor asignación de órdenes de transporte a una determinada flota de vehículos para cumplir con todas las órdenes de entrega, minimizando el costo de transporte sin dejar de considerar la capacidad máxima de cada una de las unidades. En un trabajo previo diseñamos un operador de recombinación específico para este problema con el que se obtuvieron mejores resultados que con operadores tradicionales utilizados en la literatura para resolver este problema. El objetivo de este trabajo es analizar la incorporación de nuestro operador de recombinación en un algoritmo evolutivo celular, que mostró un buen desempeño para resolver este problema. Los resultados obtenidos en este trabajo permiten suponer que la incorporación de este operador en el proceso evolutivo de un algoritmo celular logra obtener buenas soluciones al problema en estudio, y para algunas instancias analizadas mejorar el rendimiento de otras propuestas.Presentado en el X Workshop Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Algoritmos celulares con operadores específicos para resolver un problema de ruteo de vehículos

El Problema de Ruteo de Vehículos con Capacidad limitada consiste en encontrar la mejor asignación de órdenes de transporte a una determinada flota de vehículos para cumplir con todas las órdenes de entrega, minimizando el costo de transporte sin dejar de considerar la capacidad máxima de cada una de las unidades. En un trabajo previo diseñamos un operador de recombinación específico para este problema con el que se obtuvieron mejores resultados que con operadores tradicionales utilizados en la literatura para resolver este problema. El objetivo de este trabajo es analizar la incorporación de nuestro operador de recombinación en un algoritmo evolutivo celular, que mostró un buen desempeño para resolver este problema. Los resultados obtenidos en este trabajo permiten suponer que la incorporación de este operador en el proceso evolutivo de un algoritmo celular logra obtener buenas soluciones al problema en estudio, y para algunas instancias analizadas mejorar el rendimiento de otras propuestas.Presentado en el X Workshop Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

A Neuro-Evolutionary Approach to Electrocardiographic Signal Classification

International audienceThis chapter presents an evolutionary Artificial Neural Networks (ANN) classifier system as a heartbeat classification algorithm designed according to the rules of the PhysioNet/Computing in Cardiology Challenge 2011 (Moody, Comput Cardiol Challenge 38:273-276, 2011), whose aim is to develop an efficient algorithm able to run within a mobile phone that can provide useful feedback when acquiring a diagnostically useful 12-lead Electrocardiography (ECG) recording. The method used to solve this problem is a very powerful natural computing analysis tool, namely evolutionary neural networks, based on the joint evolution of the topology and the connection weights relying on a novel similarity-based crossover. The chapter focuses on discerning between usable and unusable electrocardiograms tele-medically acquired from mobile embedded devices. A preprocessing algorithm based on the Discrete Fourier Transform has been applied before the evolutionary approach in order to extract an ECG feature dataset in the frequency domain. Finally, a series of tests has been carried out in order to evaluate the performance and the accuracy of the classifier system for such a challenge

Framework for collaborative knowledge management in organizations

Nowadays organizations have been pushed to speed up the rate of industrial transformation to high value products and services. The capability to agilely respond to new market demands became a strategic pillar for innovation, and knowledge management could support organizations to achieve that goal. However, current knowledge management approaches tend to be over complex or too academic, with interfaces difficult to manage, even more if cooperative handling is required. Nevertheless, in an ideal framework, both tacit and explicit knowledge management should be addressed to achieve knowledge handling with precise and semantically meaningful definitions. Moreover, with the increase of Internet usage, the amount of available information explodes. It leads to the observed progress in the creation of mechanisms to retrieve useful knowledge from the huge existent amount of information sources. However, a same knowledge representation of a thing could mean differently to different people and applications. Contributing towards this direction, this thesis proposes a framework capable of gathering the knowledge held by domain experts and domain sources through a knowledge management system and transform it into explicit ontologies. This enables to build tools with advanced reasoning capacities with the aim to support enterprises decision-making processes. The author also intends to address the problem of knowledge transference within an among organizations. This will be done through a module (part of the proposed framework) for domain’s lexicon establishment which purpose is to represent and unify the understanding of the domain’s used semantic