17 research outputs found
Solving the vehicle routing problem using hybrid cellular evolutionary algorithm
Problem usmjeravanja vozila (VRP) kompleksan je kombinatorički problem s kojim se svakodnevno susreću tvrtke koje obavljaju dostavu robe. Njegovim učinkovitim rješavanjem moguće je značajno smanjiti troškove dostave. Metaheurističkim metodama moguće je relativno brzo pronaći visoko kvalitetna rješenja. Stanični evolucijski algoritam metaheuristički je algoritam kod kojeg su jedinke iz populacije raspoređene unutar toroidalne mreže i mogu biti u interakciji samo sa obližnjim jedinkama. Podešavanjem selekcijskog pritiska moguće je postići odgovarajući omjer diverzifikacije i intenzifikacije koji je ključan za uspješnost algoritma. Hibridizacija postupkom pretraživanja velikog susjedstva ubrzava pronalazak visoko kvalitetnih rješenja. Razvijeni algoritam testiran je na nekoliko skupova ispitnih zadataka te na problemima dostave hrvatskih tvrtki. Rezultati ostvareni na ispitnim zadacima pokazuju da učinkovitost algoritma ne odstupa mnogo od najboljih poznatih algoritama za ovu vrstu problema, dok rezultati ostvareni na problemima hrvatskih tvrtki pokazuju da je primjenom algoritma moguće postići značajne uštede.Vehicle Routing Problem (VRP) is a complex combinatorial problem encountered daily by companies that are dealing with goods delivery. With its ecient solving it is possible to signicantly reduce the cost of delivery. Metaheuristic methods are capable of nding high-quality solutions in reasonable amount of time. The cellular evolutionary algorithm is a metaheuristic algorithm in which the individuals from the population are distributed within the toroidal grid and can interact only with nearby entities. By adjusting the selection pressure, it is possible to achieve the appropriate ratio of diversication and intensication that is crucial to the success of the algorithm. Hybridization by a large neighborhood search accelerates the nding of high quality solutions. The developed algorithm has been tested on several sets of benchmarks and on the delivery problems of Croatian companies. The results obtained on the benchmarks show that the eciency of the algorithm does not dier much from the best-known algorithms for this type of problem, while the results achieved on the problems of Croatian companies show that it is possible to achieve signicant savings by algorithm application
Solving the vehicle routing problem using hybrid cellular evolutionary algorithm
Problem usmjeravanja vozila (VRP) kompleksan je kombinatorički problem s kojim se svakodnevno susreću tvrtke koje obavljaju dostavu robe. Njegovim učinkovitim rješavanjem moguće je značajno smanjiti troškove dostave. Metaheurističkim metodama moguće je relativno brzo pronaći visoko kvalitetna rješenja. Stanični evolucijski algoritam metaheuristički je algoritam kod kojeg su jedinke iz populacije raspoređene unutar toroidalne mreže i mogu biti u interakciji samo sa obližnjim jedinkama. Podešavanjem selekcijskog pritiska moguće je postići odgovarajući omjer diverzifikacije i intenzifikacije koji je ključan za uspješnost algoritma. Hibridizacija postupkom pretraživanja velikog susjedstva ubrzava pronalazak visoko kvalitetnih rješenja. Razvijeni algoritam testiran je na nekoliko skupova ispitnih zadataka te na problemima dostave hrvatskih tvrtki. Rezultati ostvareni na ispitnim zadacima pokazuju da učinkovitost algoritma ne odstupa mnogo od najboljih poznatih algoritama za ovu vrstu problema, dok rezultati ostvareni na problemima hrvatskih tvrtki pokazuju da je primjenom algoritma moguće postići značajne uštede.Vehicle Routing Problem (VRP) is a complex combinatorial problem encountered daily by companies that are dealing with goods delivery. With its ecient solving it is possible to signicantly reduce the cost of delivery. Metaheuristic methods are capable of nding high-quality solutions in reasonable amount of time. The cellular evolutionary algorithm is a metaheuristic algorithm in which the individuals from the population are distributed within the toroidal grid and can interact only with nearby entities. By adjusting the selection pressure, it is possible to achieve the appropriate ratio of diversication and intensication that is crucial to the success of the algorithm. Hybridization by a large neighborhood search accelerates the nding of high quality solutions. The developed algorithm has been tested on several sets of benchmarks and on the delivery problems of Croatian companies. The results obtained on the benchmarks show that the eciency of the algorithm does not dier much from the best-known algorithms for this type of problem, while the results achieved on the problems of Croatian companies show that it is possible to achieve signicant savings by algorithm application
Solving the vehicle routing problem using hybrid cellular evolutionary algorithm
Problem usmjeravanja vozila (VRP) kompleksan je kombinatorički problem s kojim se svakodnevno susreću tvrtke koje obavljaju dostavu robe. Njegovim učinkovitim rješavanjem moguće je značajno smanjiti troškove dostave. Metaheurističkim metodama moguće je relativno brzo pronaći visoko kvalitetna rješenja. Stanični evolucijski algoritam metaheuristički je algoritam kod kojeg su jedinke iz populacije raspoređene unutar toroidalne mreže i mogu biti u interakciji samo sa obližnjim jedinkama. Podešavanjem selekcijskog pritiska moguće je postići odgovarajući omjer diverzifikacije i intenzifikacije koji je ključan za uspješnost algoritma. Hibridizacija postupkom pretraživanja velikog susjedstva ubrzava pronalazak visoko kvalitetnih rješenja. Razvijeni algoritam testiran je na nekoliko skupova ispitnih zadataka te na problemima dostave hrvatskih tvrtki. Rezultati ostvareni na ispitnim zadacima pokazuju da učinkovitost algoritma ne odstupa mnogo od najboljih poznatih algoritama za ovu vrstu problema, dok rezultati ostvareni na problemima hrvatskih tvrtki pokazuju da je primjenom algoritma moguće postići značajne uštede.Vehicle Routing Problem (VRP) is a complex combinatorial problem encountered daily by companies that are dealing with goods delivery. With its ecient solving it is possible to signicantly reduce the cost of delivery. Metaheuristic methods are capable of nding high-quality solutions in reasonable amount of time. The cellular evolutionary algorithm is a metaheuristic algorithm in which the individuals from the population are distributed within the toroidal grid and can interact only with nearby entities. By adjusting the selection pressure, it is possible to achieve the appropriate ratio of diversication and intensication that is crucial to the success of the algorithm. Hybridization by a large neighborhood search accelerates the nding of high quality solutions. The developed algorithm has been tested on several sets of benchmarks and on the delivery problems of Croatian companies. The results obtained on the benchmarks show that the eciency of the algorithm does not dier much from the best-known algorithms for this type of problem, while the results achieved on the problems of Croatian companies show that it is possible to achieve signicant savings by algorithm application
Historia, evolución y perspectivas de futuro en la utilización de técnicas de simulación en la gestión portuaria: aplicaciones en el análisis de operaciones, estrategia y planificación portuaria
Programa Oficial de Doutoramento en Análise Económica e Estratexia Empresarial. 5033V0[Resumen]
Las técnicas de simulación, tal y como hoy las conocemos, comenzaron a mediados del siglo
XX; primero con la aparición del primer computador y el desarrollo del método Monte Carlo, y
más tarde con el desarrollo del primer simulador de propósito específico conocido como GPS y
desarrollado por Geoffrey Gordon en IBM y la publicación del primer texto completo dedicado a
esta materia y llamado the Art of Simulation (K.D. Tocher, 1963).
Estás técnicas han evolucionado de una manera extraordinaria y hoy en día están plenamente
implementadas en diversos campos de actividad.
Las instalaciones portuarias no han escapado de esta tendencia, especialmente las dedicadas al
tráfico de contenedores.
Efectivamente, las características intrínsecas de este sector económico, le hacen un candidato
idóneo para la implementación de modelos de simulación con propósitos y alcances muy diversos.
No existe, sin embargo y hasta lo que conocemos, un trabajo científico que compile y analice
pormenorizadamente tanto la historia como la evolución de simulación en ambientes portuarios,
ayudando a clasificar los mismos y determinar cómo estos pueden ayudar en el análisis económico
de estas instalaciones y en la formulación de las oportunas estrategias empresariales.
Este es el objetivo último de la presente tesis doctoral.[Resumo]
As técnicas de simulación, tal e como hoxe as coñecemos, comezaron a mediados do século XX;
primeiro coa aparición do computador e o desenvolvemento do método Monte Carlo e máis tarde
co desenvolvemento do primeiro simulador de propósito específico coñecido como GPS e
desenvolvido por Geoffrey Gordon en IBM e a publicación do primeiro texto completo dedicado
a este tema chamado “A Arte da Simulación” (K.D. Tocher, 1963).
Estas técnicas evolucionaron dun xeito extraordinario e hoxe en día están plenamente
implementadas en diversos campos de actividade.
As instalacións portuarias non escaparon desta tendencia, especialmente as dedicadas ao tráfico
de contenedores.
Efectivamente, as características intrínsecas deste sector económico, fanlle un candidato idóneo
para a implementación de modelos de simulación con propósitos e alcances moi variados.
Con todo, e ata o que coñecemos, non existe un traballo científico que compila e analiza de forma
detallada tanto a historia como a evolución da simulación en estes ambientes portuarios,
clasificando os mesmos e determinando como estes poden axudar na análise económica destas
instalacións e na formulación das oportunas estratexias empresariais.
Este é o último obxectivo da presente tese doutoral.[Abstract]
Simulation, to the extend that we understand it nowadays, began in the middle of the 20th century;
first with the appearance of the computer and the development of the Monte Carlo method, and
later with the development of the first specific purpose simulator known as GPS developed by
Geoffrey Gordon in IBM. This author published the first full text devoted to this subject “The Art
of Simulation” in 1963.
These techniques have evolved in an extraordinary way and nowadays they are fully implemented
in different fields of activity.
Port facilities have not escaped this trend, especially those dedicated to container traffic.
Indeed, the intrinsic characteristics of this economic sector, make it a suitable candidate for the
implementation of simulation with very different purposes and scope.
However, to the best of our knowelegde, there is not a scientific work that compiles and analyzes
in detail both, the history and the evolution of simulation in port environments, contributing to
classify them and determine how they can help in the economic analysis of these facilities and in
the formulation of different business strategies.
This is the ultimate goal of this doctoral thesis
Solving hard subgraph problems in parallel
This thesis improves the state of the art in exact, practical algorithms for finding subgraphs. We study maximum clique, subgraph isomorphism, and maximum common subgraph problems. These are widely applicable: within computing science, subgraph problems arise in document clustering, computer vision, the design of communication protocols, model checking, compiler code generation, malware detection, cryptography, and robotics; beyond, applications occur in biochemistry, electrical engineering, mathematics, law enforcement, fraud detection, fault diagnosis, manufacturing, and sociology. We therefore consider both the ``pure'' forms of these problems, and variants with labels and other domain-specific constraints.
Although subgraph-finding should theoretically be hard, the constraint-based search algorithms we discuss can easily solve real-world instances involving graphs with thousands of vertices, and millions of edges. We therefore ask: is it possible to generate ``really hard'' instances for these problems, and if so, what can we learn? By extending research into combinatorial phase transition phenomena, we develop a better understanding of branching heuristics, as well as highlighting a serious flaw in the design of graph database systems.
This thesis also demonstrates how to exploit two of the kinds of parallelism offered by current computer hardware. Bit parallelism allows us to carry out operations on whole sets of vertices in a single instruction---this is largely routine. Thread parallelism, to make use of the multiple cores offered by all modern processors, is more complex. We suggest three desirable performance characteristics that we would like when introducing thread parallelism: lack of risk (parallel cannot be exponentially slower than sequential), scalability (adding more processing cores cannot make runtimes worse), and reproducibility (the same instance on the same hardware will take roughly
the same time every time it is run). We then detail the difficulties in guaranteeing these characteristics when using modern algorithmic techniques.
Besides ensuring that parallelism cannot make things worse, we also increase the likelihood of it making things better. We compare randomised work stealing to new tailored strategies, and perform experiments to identify the factors contributing to good speedups. We show that whilst load balancing is difficult, the primary factor influencing the results is the interaction between branching heuristics and parallelism. By using parallelism to explicitly offset the commitment made to weak early branching choices, we obtain parallel subgraph solvers which are substantially and consistently better than the best sequential algorithms
Parallel memetic algorithms for the problem of workforce distribution in dynamis multi-agent system
Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Arquitectura de Computadores y Automática, leída el 20/09/2013Esta tesis describe un novedoso enfoque para resolver el problema de distribución de carga de trabajo en sistemas multi-agente dinámicos basados en arquitecturas de pizarra, enfocándose especialmente en un escenario real: el call center multitarea. Para abordar este tipo de entornos dinámicos, tradicionalmente se han aplicado diversas
heurísticas voraces que permiten dar una solución en tiempo real. Básicamente, dichas heurísticas realizan planificaciones continuamente, considerando el estado del
sistema en cada momento. Como las decisiones se toman de forma voraz sin hacer una planificación óptima, la distribución de la carga de trabajo puede ser pobre a
medio y/o largo plazo. El uso de algoritmos meméticos paralelos nos puede permitir encontrar soluciones mucho más precisas. Para aplicar este tipo de algoritmos, introducimos
el concepto de ventana temporal adaptativa. De esta forma, el tamaño de la ventana temporal depende del nivel de dinamismo del sistema en un instante dado. Este trabajo propone una serie de herramientas para determinar el dinamismo del sistema de forma automática, así como un novedoso módulo de predicción basado en una red neuronal y un potente método de búsqueda basado en meta-algoritmos
meméticos paralelos para poder lidiar con entornos dinámicos complejos. Para concluir, comparamos nuestro enfoque con otras técnicas del estado del arte en un entorno
de producción real (Telefónica) obteniendo mejores resultados que el resto de técnicas actuales. También se proporciona un estudio exhaustivo de cada uno de los módulos.Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaTRUEunpu
Anales del XIII Congreso Argentino de Ciencias de la Computación (CACIC)
Contenido:
Arquitecturas de computadoras
Sistemas embebidos
Arquitecturas orientadas a servicios (SOA)
Redes de comunicaciones
Redes heterogéneas
Redes de Avanzada
Redes inalámbricas
Redes móviles
Redes activas
Administración y monitoreo de redes y servicios
Calidad de Servicio (QoS, SLAs)
Seguridad informática y autenticación, privacidad
Infraestructura para firma digital y certificados digitales
Análisis y detección de vulnerabilidades
Sistemas operativos
Sistemas P2P
Middleware
Infraestructura para grid
Servicios de integración (Web Services o .Net)Red de Universidades con Carreras en Informática (RedUNCI