In this thesis we formulate joint cell, channel and power allocation problems within wireless communication networks. The objectives are to maximize the user with mini- mum data throughput (Shannon capacity) or to maximize the total system throughput, referred to as the max-min and max-sum problem respectively. The complexity is stud- ied together with proposed optimization- and heuristic-based approaches. In the first paper an overall joint cell, channel and power allocation max-min prob- lem is formulated. We show that the decision problem is NP-hard and that the op- timization problem is not approximable unless P is equal to NP, for instances with a sufficiently large number of channels. Further, it follows that for a feasible binary cell and channel allocation, the remaining continuous power allocation optimization problem is still not approximable unless P is equal to NP. In addition, it is shown that first-order optimality conditions give global optimum of the single channel power al- location optimization problem, although the problem is in general not convex. In the following two papers heuristics for solving the overall problem are proposed. In the second paper we consider the single channel problem with convex combinations of the max-min and the max-sum objective functions. This variable utility provides the ability of tuning the amount of fairness and total throughput. The third paper investi- gates the multiple channel setting. On a system with three cells, eight mobile users and three channels, we perform an exhaustive search over feasible cell and channel alloca- tions. The exhaustive search is then compared to the less computationally expensive heuristic approaches, presenting potential earnings to strive for. A conclusion is that several of the proposed heuristics perform very well. The final paper incorporates fixed relay stations into the overall joint cell, channel and power allocation max-min problem. The complexity is inherited from the formula- tion without relay stations. Further, we propose a heuristic channel allocation approach that shows good performance, compared to an optimization based approach, in numer- ical simulations on the relay setting. / Financial support by the Swedish Foundation for Strategic Research (SSF) QC 20110915

Otimização estrutural é uma área relativamente nova que vem sendo cada vez mais explorada. Existem muitos métodos clássicos, e outros mais recentes vem surgindo para disputar em eficiência, confiabilidade e rapidez na obtenção de um resultado ótimo. Os algoritmos são classificados em algoritmos determinísticos, que utilizam a informação do gradiente, ou seja, usam os valores das funções e suas derivadas, e os meta-heurísticos, algoritmos de otimização aleatórios que são métodos probabilísticos não baseados em gradiente, ou seja, usam somente a avaliação da função objetivo. São apresentados dois algoritmos meta-heurísticos relativamente recentes: o Harmony Search, baseado na improvisação musical em busca da harmonia perfeita, e o Firefly Algorithm, que é inspirado no comportamento da luz dos vagalumes. Vários exemplos clássicos de treliças 2-D e 3-D considerando otimização paramétrica e de forma, com restrições de tensão, deslocamento, flambagem e frequência natural, são apresentados para demonstrar a eficiência dos métodos. Os resultados são comparados aos de outros autores usando diferentes métodos encontrados na literatura. Os resultados indicam que os algoritmos de otimização estudados neste trabalho são melhores ou tão eficientes quanto os demais. Por fim, os métodos são aplicados à estrutura de um projeto de engenharia adaptado. / Structural optimization is a relatively new area that has been increasingly exploited. There are many classical methods, and newer are emerging to compete on efficiency, reliability and speed in obtaining an optimal result. The algorithms are classified into deterministic algorithms, which use the gradient information, i.e., use the values of the functions and their derivatives, and meta-heuristic algorithms, random optimization methods which are probabilistic methods not based on gradient, i.e., they use only objective function evaluation. Two relatively recent meta-heuristics algorithms are presented, Harmony Search, based on musical improvisation in search of the perfect harmony, and Firefly Algorithm, which is inspired by the behavior of the light of fireflies. Several benchmarks of 2-D and 3-D trusses considering size and shape optimization, with stress, displacement, buckling and natural frequency constraints, are presented to demonstrate the effectiveness of the methods. The results are compared to the others authors using different methods found in the literature. The results indicate that optimization algorithms studied in this work are better than or as efficient as others. Finally, the methods are applied to the structure of an adapted engineering design.

Orientador: Cid Carvalho de Souza / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-19T00:16:31Z (GMT). No. of bitstreams: 1 Zilli_PetersonKatagiri_M.pdf: 1307926 bytes, checksum: 5fe0ddfca7cce84d9e26b66106d61e8b (MD5) Previous issue date: 2011 / Resumo: O Problema de Roteamento de Veículos (VRP, em inglês) foi proposto por Dantzig e Ramser em 1959 e, desde então, um grande número de artigos foi dedicado à solução de suas variantes. O problema original consiste em determinar rotas otimais que serão usadas por veículos de capacidade limitada para servirem a um conjunto de clientes. Neste trabalho focamos o estudo e a implementação dos modelos chamados de "ricos" na literatura, os quais englobam variantes complexas do VRP e conseguem representar situações mais próximas dos problemas logísticos encontrados em sistemas de distribuição reais. A principal motivação para esta pesquisa é uma aplicação prática referente ao problema de roteamento dos ônibus fretados pela UNICAMP para o transporte de seus funcionários, que se caracteriza como um modelo rico. O objetivo final é a otimização de tal processo através da minimização da distância total percorrida ou do número de veículos empregados, com a consequente redução dos gastos incorridos pela Universidade. Portanto, além do seu aspecto científico, esta dissertação produz resultados com chances reais de trazer benefícios à administração de uma instituição pública de ensino. Para que isto venha a ocorrer, as heurísticas desenvolvidas foram inseridas em um sistema de informações geográficas, que será usado pela universidade no processo de criação e otimização das rotas a serem licitadas publicamente / Abstract: The Vehicle Routing Problem (VRP) was first proposed by Dantzig and Ramser in 1959 and, since then, a large number of papers has been devoted to the solution of its variants. The original problem consists in determining an optimal set of routes to be used by vehicles of limited capacity that serve a set of customers. In this paper we focus on the study and implementation of models called "rich" in the literature, which include complex variants of the VRP that represent situations closer to the logistical problems encountered in real distribution systems. The main motivation for this research is a practical problem concerning the routing of buses chartered by UNICAMP for transporting a part of its employees, which is characterized as a rich model. The goal is to optimize this process by minimizing the total travel distance or the number of vehicles used, with a consequent reduction of the expenses incurred by the University. Therefore, in addition to its scientific aspect, this dissertation gives results with real chances to benefit the administration of a public university. For this to happen, the heuristics developed were entered into a geographic information system, which will be used by the university in the process of creation and optimization of routes to be publicly auctioned / Mestrado / Pesquisa Operacional / Mestre em Ciência da Computação

Increasing waste production is the reason why it is important to focus in more detail on profitable and cost side of waste economy. This diploma thesis deals with the area of garbage collection as a fundamental part during garbage their cumulation in a particular location and follow-up liquidation or preservation. At first the theoretical background of Chinese Postman Problem is described as a cornerstone for garbage collection models. Extensions of this problem have to be considered to be closer to reality. Then waste management in the city of Poděbrady is thoroughly described. In the final part of diploma thesis aforementioned theoretical models are applied on real data obtained from the city of Poděbrady waste department. Heuristic algorithms are an essential part of thesis as a replacement of optimizations models that cannot be used in some cases due to high requirements on computational time.

Otimização estrutural é uma área relativamente nova que vem sendo cada vez mais explorada. Existem muitos métodos clássicos, e outros mais recentes vem surgindo para disputar em eficiência, confiabilidade e rapidez na obtenção de um resultado ótimo. Os algoritmos são classificados em algoritmos determinísticos, que utilizam a informação do gradiente, ou seja, usam os valores das funções e suas derivadas, e os meta-heurísticos, algoritmos de otimização aleatórios que são métodos probabilísticos não baseados em gradiente, ou seja, usam somente a avaliação da função objetivo. São apresentados dois algoritmos meta-heurísticos relativamente recentes: o Harmony Search, baseado na improvisação musical em busca da harmonia perfeita, e o Firefly Algorithm, que é inspirado no comportamento da luz dos vagalumes. Vários exemplos clássicos de treliças 2-D e 3-D considerando otimização paramétrica e de forma, com restrições de tensão, deslocamento, flambagem e frequência natural, são apresentados para demonstrar a eficiência dos métodos. Os resultados são comparados aos de outros autores usando diferentes métodos encontrados na literatura. Os resultados indicam que os algoritmos de otimização estudados neste trabalho são melhores ou tão eficientes quanto os demais. Por fim, os métodos são aplicados à estrutura de um projeto de engenharia adaptado. / Structural optimization is a relatively new area that has been increasingly exploited. There are many classical methods, and newer are emerging to compete on efficiency, reliability and speed in obtaining an optimal result. The algorithms are classified into deterministic algorithms, which use the gradient information, i.e., use the values of the functions and their derivatives, and meta-heuristic algorithms, random optimization methods which are probabilistic methods not based on gradient, i.e., they use only objective function evaluation. Two relatively recent meta-heuristics algorithms are presented, Harmony Search, based on musical improvisation in search of the perfect harmony, and Firefly Algorithm, which is inspired by the behavior of the light of fireflies. Several benchmarks of 2-D and 3-D trusses considering size and shape optimization, with stress, displacement, buckling and natural frequency constraints, are presented to demonstrate the effectiveness of the methods. The results are compared to the others authors using different methods found in the literature. The results indicate that optimization algorithms studied in this work are better than or as efficient as others. Finally, the methods are applied to the structure of an adapted engineering design.

There is no doubt Medical Devices have a crucial role in hospital processes such as surgeries and therapeutic procedures. Medical devices available in hospitals are of two types; reusable and non-resalable medical devices. Reusable medical devices are washed and sterilized after each use. The process of sterilizing medical devices is performed in the sterilization department. Each medical device travels through a cycle each time it is utilized. It is explicit that any part of the sterilization cycle that delays the process can cause serious problems for hospitals’ performance. The washing step of the sterilization process has been a bottleneck in the system. Thus, optimization approaches can be highly advantageous to improve this bottleneck. The data of the medical devices are usually unknown prior to the scheduling process since the finishing time of the surgeries are not known in advance. Thus, there is no information available on the ready time of medical devices to be sterilized. Due to this factor, to develop applicable solutions, it is critical to consider this problem as an online problem and develop online scheduling methods. In this thesis, we take advantage of mathematical programming and heuristic algorithms to solve both the offline and online settings of the problem. We model the washing step of the sterilization cycle as a scheduling problem. Batch scheduling and bin packing, two well-known optimization approaches, are used for this purpose. Medical devices are batched together first and then scheduled on machines to reduce the total washing time of all medical devices. First, a mathematical model for the offline problem is provided and tested to solve the problem. Then a series of heuristic algorithms are developed using the batch scheduling approach for solving both offline and online problems. Moreover, a special case with divisible job sizes and equal release dates is studied. It was proved that for the strongly divisible sequence the First Fit Increasing algorithm finds the optimal solution, also for the weakly divisible sequence a Dynamic Programming algorithm is developed. Finally, we couple optimization with simulation to test the impact of the optimization of the washing step on the entire sterilization system. Moreover, since the next step of the sterilization cycle, the sterilization step, is very similar to the washing step, we also implement the developed heuristics in this step to evaluate its performance and improve it further. The results show that as long as the washing step is optimized it does not differ which algorithm is used in the sterilization step, thus, the optimization of this step is not necessary.

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Yes / In this paper, we report the results of our recent research into the understanding of the exact distribution of a smile across the face, especially the distinction in the weight distribution of a smile between a genuine and a posed smile. To do this, we have developed a computational framework for the analysis of the dynamic motion of various parts of the face during a facial expression, in particular, for the smile expression. The heart of our dynamic smile analysis framework is the use of optical flow intensity variation across the face during a smile. This can be utilised to efficiently map the dynamic motion of individual regions of the face such as the mouth, cheeks and areas around the eyes. Thus, through our computational framework, we infer the exact distribution of weights of the smile across the face. Further, through the utilisation of two publicly available datasets, namely the CK+ dataset with 83 subjects expressing posed smiles and the MUG dataset with 35 subjects expressing genuine smiles, we show there is a far greater activity or weight distribution around the regions of the eyes in the case of a genuine smile. / Supported in part by the European Union's Horizon 2020 Programme H2020-MSCA-RISE-2017, under the project PDE-GIR with grant number 778035.

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