A hybrid method that addresses the design and optimization of long-span steel trusses is presented. By utilizing advancements in present day computing and biologically inspired analysis and design, an effort has been made to automate the process of evolving optimal trusses in an unstructured problem domain. Topology, geometry and sizing optimization of trusses are simultaneously addressed using a three stage methodology. Multi-objective genetic algorithms are used to optimize the member section sizes of truss topologies and geometries. Converting constraints into additional objectives provides a robust algorithm that results in improved convergence to the pareto-optimal set of solutions. In addition, the pareto-curve plotted based on how well the different objectives are satisfied helps in identifying the trade-offs that exist between these objectives, while also providing an efficient way to rank the population of solutions during the search process. A comparison study between multi-objective genetic algorithms, simulated annealing, and reactive taboo search is conducted to evaluate the efficiency of each method with relation to its overall performance, computational expense, sensitivity to initial parameter settings, and repeatability of finding near-global optimal designs. The benefit of using a three stage approach, and also implementing the entire model on parallel computers, is the high level of computational efficiency that is obtained for the entire process and the near-optimal solutions obtained. The overall efficiency and effectiveness of this method has been established by comparing the truss design results obtained using this method on bridge and roof truss benchmark problems with truss designs obtained by other researchers. One of the salient features of thisresearch is the large number of optimal trusses that are produced as the final result. The range of designs available provides the user with the flexibility to select the truss design that best matches their design requirements. By supporting human-computer interactions between these stages, the program also incorporates subjective aesthetic criteria, which assist in producing final designs in consonance with the user's requirements.

This Thesis Work will concentrate on a very interesting problem, the Vehicle Routing Problem (VRP). In this problem, customers or cities have to be visited and packages have to be transported to each of them, starting from a basis point on the map. The goal is to solve the transportation problem, to be able to deliver the packages-on time for the customers,-enough package for each Customer,-using the available resources- and – of course - to be so effective as it is possible.Although this problem seems to be very easy to solve with a small number of cities or customers, it is not. In this problem the algorithm have to face with several constraints, for example opening hours, package delivery times, truck capacities, etc. This makes this problem a so called Multi Constraint Optimization Problem (MCOP). What’s more, this problem is intractable with current amount of computational power which is available for most of us. As the number of customers grow, the calculations to be done grows exponential fast, because all constraints have to be solved for each customers and it should not be forgotten that the goal is to find a solution, what is best enough, before the time for the calculation is up. This problem is introduced in the first chapter: form its basics, the Traveling Salesman Problem, using some theoretical and mathematical background it is shown, why is it so hard to optimize this problem, and although it is so hard, and there is no best algorithm known for huge number of customers, why is it a worth to deal with it. Just think about a huge transportation company with ten thousands of trucks, millions of customers: how much money could be saved if we would know the optimal path for all our packages.Although there is no best algorithm is known for this kind of optimization problems, we are trying to give an acceptable solution for it in the second and third chapter, where two algorithms are described: the Genetic Algorithm and the Simulated Annealing. Both of them are based on obtaining the processes of nature and material science. These algorithms will hardly ever be able to find the best solution for the problem, but they are able to give a very good solution in special cases within acceptable calculation time.In these chapters (2nd and 3rd) the Genetic Algorithm and Simulated Annealing is described in details, from their basis in the “real world” through their terminology and finally the basic implementation of them. The work will put a stress on the limits of these algorithms, their advantages and disadvantages, and also the comparison of them to each other.Finally, after all of these theories are shown, a simulation will be executed on an artificial environment of the VRP, with both Simulated Annealing and Genetic Algorithm. They will both solve the same problem in the same environment and are going to be compared to each other. The environment and the implementation are also described here, so as the test results obtained.Finally the possible improvements of these algorithms are discussed, and the work will try to answer the “big” question, “Which algorithm is better?”, if this question even exists.

A hybrid method that addresses the design and optimization of long-span steel trusses is presented. By utilizing advancements in present day computing and biologically inspired analysis and design, an effort has been made to automate the process of evolving optimal trusses in an unstructured problem domain. Topology, geometry and sizing optimization of trusses are simultaneously addressed using a three stage methodology. Multi-objective genetic algorithms are used to optimize the member section sizes of truss topologies and geometries. Converting constraints into additional objectives provides a robust algorithm that results in improved convergence to the pareto-optimal set of solutions. In addition, the pareto-curve plotted based on how well the different objectives are satisfied helps in identifying the trade-offs that exist between these objectives, while also providing an efficient way to rank the population of solutions during the search process. A comparison study between multi-objective genetic algorithms, simulated annealing, and reactive taboo search is conducted to evaluate the efficiency of each method with relation to its overall performance, computational expense, sensitivity to initial parameter settings, and repeatability of finding near-global optimal designs. The benefit of using a three stage approach, and also implementing the entire model on parallel computers, is the high level of computational efficiency that is obtained for the entire process and the near-optimal solutions obtained. The overall efficiency and effectiveness of this method has been established by comparing the truss design results obtained using this method on bridge and roof truss benchmark problems with truss designs obtained by other researchers. One of the salient features of thisresearch is the large number of optimal trusses that are produced as the final result. The range of designs available provides the user with the flexibility to select the truss design that best matches their design requirements. By supporting human-computer interactions between these stages, the program also incorporates subjective aesthetic criteria, which assist in producing final designs in consonance with the user's requirements.

La lithographie et la loi de Moore ont permis des avancées extraordinaires dans la fabrication des circuits intégrés. De nos jours, plusieurs systèmes très complexes peuvent être embarqués sur la même puce électronique. Les contraintes de développement de ces systèmes sont tellement grandes qu’une bonne planification dès le début de leur cycle de développement est incontournable. Ainsi, la planification de la gestion énergétique au début du cycle de développement est devenue une phase importante dans la conception de ces systèmes. Pendant plusieurs années, l’idée était de réduire la consommation énergétique en ajoutant un mécanisme physique une fois le circuit créé, comme par exemple un dissipateur de chaleur. La stratégie actuelle est d’intégrer les contraintes énergétiques dès les premières phases de la conception des circuits. Il est donc essentiel de bien connaître la dissipation d’énergie avant l’intégration des composantes dans une architecture d’un système multiprocesseurs de façon à ce que chaque composante puisse fonctionner efficacement dans les limites de ses contraintes thermiques. Lorsqu’une composante fonctionne, elle consomme de l’énergie électrique qui est transformée en dégagement de chaleur. Le but de ce mémoire est de trouver une affectation efficace des composantes dans une architecture de multiprocesseurs en trois dimensions en tenant compte des limites des facteurs thermiques de ce système. / Lithography and Moore’s law have led to extraordinary advances in integrated circuits manufacturing. Nowadays, many complex systems can be embedded on the same chip. Development constraints of these systems are so significant that a good planning from the beginning of the development stage is essential. Thus, the planning of energy management at the beginning of the development cycle has become important in the design of these systems. For several years, the idea was to reduce energy consumption by adding a cooling system once the circuit is created, a heat sink for example. The current strategy is to integrate energy constraints in the early stages of circuits design. It is therefore important to know the energy dissipation before the integration of the components in the architecture of a multiprocessor system so that each component can work within the limits of its thermal stresses. When a component is running, it consumes electric energy which is converted into heat. The aim of this thesis is to find an efficient assignment of components in a multiprocessor system architecture in three dimensions, taking into account the limits of its thermal factors.

Made available in DSpace on 2014-12-17T14:52:44Z (GMT). No. of bitstreams: 1 WernerKSS.pdf: 2229557 bytes, checksum: 7a64dc1b94612cd78d88c6eb822d29e6 (MD5) Previous issue date: 2009-10-31 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / The SONET/SDH Ring Assignment Problem (PALAS) treats to group localities in form of some rings, being respected the traffic's limitations of the equipment. Each ring uses a DXC (Digital Cross Connect) to make the communication with the others, being the DXC the equipment most expensive of the net, minimizing the number total of rings, will minimize the total net cost, problem's objective . This topology in rings provides a bigger capacity of regeneration. The PALAS is a problem in Combinatorial Optimization of NP-hard Class. It can be solved through Heuristics and Metaheuristics. In this text, we use Taboo Search while we keep a set of elite solutions to be used in the formation of a part of the collection of vocabulary's parts that in turn will be used in the Vocabulary Building. The Vocabulary Building will be started case Taboo Search does not reach the best solution for the instance. Three approaches had been implemented: one that only uses vocabulary's parts deriving of Taboo Search, one that it only uses vocabulary's parts randomly generated and a last one that it uses half come of the elite and half randomly generated / O Problema da Atribui??o de Localidades a An?is em Redes SONET/SDH (PALAS) trata de agrupar localidades em forma de v?rios an?is, respeitando as limita??es de tr?fego dos equipamentos. Cada anel utiliza um DXC (Digital Cross Connect) para fazer a comunica??o com os outros, sendo o DXC o equipamento mais caro da rede, minimizando o total de an?is, minimizaremos o custo total, objetivo do problema. Essa topologia em an?is proporciona uma maior capacidade de regenera??o. O PALAS ? um problema de Otimiza??o Combinat?ria da Classe NP-dif?cil. Pode ser resolvido atrav?s de Heur?sticas e Metaheur?sticas. Neste trabalho, utilizamos a Busca Tabu enquanto guardamos um conjunto de solu??es elite para serem utilizadas na forma??o de uma parte da cole??o de voc?bulos que por sua vez ser?o usados na Constru??o de Vocabul?rio para a solu??o desse problema. A Constru??o de Vocabul?rio ser? acionada caso a Busca Tabu n?o atinja o ?timo para a inst?ncia. Foram implementadas tr?s abordagens: uma que utiliza somente voc?bulos oriundos da Busca Tabu, uma que utiliza somente voc?bulos gerados aleatoriamente e uma ?ltima que utiliza metade vinda da elite e metade aleat?ria