<p>Embedded computing systems in portable devices need to be energy efficient, yet they have to deliver adequate performance to the often computationally expensive applications. Dynamic voltage scaling is a technique that offers a speed versus power trade-off, allowing the application to achieve considerable energy savings and, at the same time, to meet the imposed time constraints.</p><p>In this thesis, we explore the possibility of using optimal voltage scaling algorithms based on nonlinear programming at the system level, for a complex multiprocessor scheduling problem. We present an optimization approach to the modeled nonlinear programming formulation of the continuous voltage selection problem excluding the consideration of transition overheads. Our approach achieves the same optimal results as the previous work using the same model, but due to its speed, can be efficiently used for design space exploration. We validate our results using numerous automatically generated benchmarks.</p>

Embedded computing systems in portable devices need to be energy efficient, yet they have to deliver adequate performance to the often computationally expensive applications. Dynamic voltage scaling is a technique that offers a speed versus power trade-off, allowing the application to achieve considerable energy savings and, at the same time, to meet the imposed time constraints. In this thesis, we explore the possibility of using optimal voltage scaling algorithms based on nonlinear programming at the system level, for a complex multiprocessor scheduling problem. We present an optimization approach to the modeled nonlinear programming formulation of the continuous voltage selection problem excluding the consideration of transition overheads. Our approach achieves the same optimal results as the previous work using the same model, but due to its speed, can be efficiently used for design space exploration. We validate our results using numerous automatically generated benchmarks.

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Cette thèse traite le développement d'un modèle mathématique d'optimisation acoustique des trajectoires de vol de deux avions commerciaux en approche sous contrainte énergétique, aérodynamique et opérationnelle. C'est un modèle analytique de contrôle optimal non-linéaire et non-convexe régi par un système d'équations différentielles ordinaires issues de la dynamique de vol et des contraintes associées. Notre contribution porte sur la modélisation mathématique des équations, l'optimisation et la programmation algorithmique d'un modèle d'optimisation non-linéaire du bruit de deux avions en approche simultanée. Les points abordés sont le développement mathématique du modèle 3D "exact" de leur dynamique de vol, la modélisation mathématique de la commande optimale de ce système dynamique, l'introduction de la consommation du carburant par les avions comme une équation différentielle avec une fonction consommation spécifique variable en fonction de l'évolution de leur dynamique, la modélisation mathématique instantanée de la fonction objectif représentant le bruit global des deux avions en approche. Sa résolution porte sur la méthode directe de programmation séquentielle quadratique avec régions de confiance sous AMPL et KNITRO. Une méthode indirecte a été appliquée sous le principe de maximum de Pontryagin suivie d'une discrétisation de type Runge-Kutta partition-née symplectique d'ordre 4 afin de démontrer la commutation entre l'approche directe et l'approche indirecte. Les résultats obtenus confirment des trajectoires optimales en descente continue, réduisant le bruit au sol ainsi que la consommation de kérosène de deux avions

Today, many small aerodromes have a hard time surviving economically, and amongst the largest cost is air traffic control. Airlines are cutting costs where they can, and many times this affects the aerodromes as well, e.g. when airlines decide to park remotely instead of at the gate. The project called Remotely Operated Towers, initiated by SESAR and run by Saab and LFV, is aiming to address this problem. The project revolves around remotely providing ATS to aerodromes where it is deemed suitable. A big challenge in this project is how to assign aerodromes to remote tower modules in the remote control centre. There are many ways to do this, but there is only a few ways to do it to achieve the least amount of modules. This thesis aims to find an optimal solution to the challenge mentioned above. The thesis resulted in a model where the user can provide the input of choice, i.e. aerodromes with associated ATS operating hours and movements, for a specific period – and receive the assignment schedule for the modules, saying exactly which aerodrome are to be controlled by which module at what time.

Abstract The removal of overlying waste rock in open pit mines to dumps is conventionally undertaken by draglines or by trucks and shovels, or by a combination of these. Waste rock dumps are the largest remnant structures of open cut mining operations and can absorb a large proportion of the mine operating costs. If the dumps are not properly developed they can be excessively expensive and can become a major safety risk and environmental hazard. There are many examples worldwide where poor design and construction of waste rock dumps have resulted in failures causing considerable loss of life and widespread damage, or have resulted in erosion and seepage that have led to severe environmental pollution. The proper design and scheduling of waste rock dumps and haul routes can significantly reduce costs, minimise the possibility of failures, and avoid harming the environment. This Thesis is limited to the consideration of trucks and shovels for waste rock haulage in open cut mining operations. It describes the development and application of a waste rock dump scheduling model using the Operations Research technique of Mixed-Integer Linear Programming, implemented in the mathematical modelling language AMPL. The model focuses on minimising the haulage cost for each block of waste rock taken from the open pit and placed in the dump. Allowance is made for the selective placement of benign and reactive waste rock, based on an open pit block model that delineates benign and reactive waste rock. The formulation requires input data including the xyz-coordinates of the block model for the open pit, information on whether the waste rock blocks are benign or reactive, the proposed time scheduling of waste rock haulage from the open pit, unit haulage costs, and the geometry of the waste rock dump, including the delineation of the zones that are benign and those that are reactive. The model was successfully tested by using both simple test data and actual mine site data. The application of the model to a simple case confirmed that it produces results that meet the Objective Function in producing an optimal haulage time and cost, and meets the various Constraints imposed. This model for scheduling the removal of waste rock from open cut mining operations with trucks and shovels will require further research and testing and, because the results are generated in a numerical format, there will also be a need to convert them to a graphical format to facilitate their interpretation. Ultimately, it will have the potential to provide a relatively low-cost scheduling tool that meets operators’ economic, safety and environmental goals.

Submitted by MARCO ALONSO MENESES ORIONDO (mameneseso@gmail.com) on 2016-04-29T17:33:57Z No. of bitstreams: 1 Meneses - Dissertação.pdf: 4087822 bytes, checksum: dc161c85a2ac9500af836619b1f9d6f3 (MD5) / Approved for entry into archive by Felipe Augusto Arakaki (arakaki@reitoria.unesp.br) on 2016-05-02T18:55:33Z (GMT) No. of bitstreams: 1 oriondo_mam_me_ilha.pdf: 4087822 bytes, checksum: dc161c85a2ac9500af836619b1f9d6f3 (MD5) / Made available in DSpace on 2016-05-02T18:55:33Z (GMT). No. of bitstreams: 1 oriondo_mam_me_ilha.pdf: 4087822 bytes, checksum: dc161c85a2ac9500af836619b1f9d6f3 (MD5) Previous issue date: 2016-03-10 / Neste trabalho apresenta-se uma versão especializada da meta-heurística Algoritmo dos Fogos de Artifício de Busca Dinâmica com Mutação de Covariância (AFABDMC) para resolver o problema de Fluxo de Potência Ótimo (FPO) em sistemas de transmissão. No algoritmo proposto consideram-se como variáveis contínuas de controle a magnitude da tensão e a geração de potência ativa nas barras de geração e como variáveis de controle discretas o estado de operação dos shunts e a posição do comutador de taps em transformadores. Assim, o modelo para o problema é de Programação Não-Linear Inteira Mista (PNLIM). A estratégia de resolução adotada consiste em controlar, em cada iteração, os valores das variáveis de controle discretas utilizando-se a meta-heurística AFABDMC e a partir desses valores escolhidos pela meta-heurística, resolver um problema de Programação Não-Linear (PNL) que fornece os valores das variáveis de controle contínuas junto com o estado de operação do sistema. A meta-heurística AFABDMC foi escrita em linguagem MATLAB e o modelo do problema em AMPL. Os subproblemas de PNL foram resolvidos utilizando-se o solver KNITRO, sendo que a interface entre o MATLAB e o AMPL foi feita utilizando-se o AMPL API. Foram realizados testes com os sistemas IEEE de 14, 30, 57 e 118 barras e os resultados indicam que a metodologia proposta é capaz de encontrar soluções de muito boa qualidade para o problema. / In this work, a new specialized metaheuristic based on the Dynamic Search Fireworks Algorithm with Covariance Mutation (DSFWACM) is applied on the Optimal Power Flow (OPF) problem in transmission systems. In the proposed method, generator bus voltage magnitudes and active power generation are considered as continuous variables and the operating state of the shunts and transformer taps settings are considered as discrete variables. Thus, the model is a Mixed-Integer Nonlinear Programming (MINLP) problem. The adopted resolution strategy is to control, in each iteration, the value of the discrete control variables using the DSFWACM metaheuristic and from the metaheuristic’s chosen values, solve the Nonlinear Programming (NLP) problem that provides the values of the continuous control variables along with the system’s operation state. The DSFWACM metaheuristic was written in MATLAB and the problem model in AMPL. The NLP sub-problems were solved using the KNITRO solver, and the interface between MATLAB and AMPL was implemented using the AMPL API. Tests were conducted with the IEEE 14, 30, 57 and 118-bus systems and the results show that the proposed method is able to find high quality solutions to the problem. / CNPq: 132374/2011-0

Orientador: Rubén Romero Lázaro / Resumo: Neste trabalho apresenta-se uma versão especializada da meta-heurística Algoritmo dos Fogos de Artifício de Busca Dinâmica com Mutação de Covariância (AFABDMC) para resolver o problema de Fluxo de Potência Ótimo (FPO) em sistemas de transmissão. No algoritmo proposto consideram-se como variáveis contínuas de controle a magnitude da tensão e a geração de potência ativa nas barras de geração e como variáveis de controle discretas o estado de operação dos shunts e a posição do comutador de taps em transformadores. Assim, o modelo para o problema é de Programação Não-Linear Inteira Mista (PNLIM). A estratégia de resolução adotada consiste em controlar, em cada iteração, os valores das variáveis de controle discretas utilizando-se a meta-heurística AFABDMC e a partir desses valores escolhidos pela meta-heurística, resolver um problema de Programação Não-Linear (PNL) que fornece os valores das variáveis de controle contínuas junto com o estado de operação do sistema. A meta-heurística AFABDMC foi escrita em linguagem MATLAB e o modelo do problema em AMPL. Os subproblemas de PNL foram resolvidos utilizando-se o solver KNITRO, sendo que a interface entre o MATLAB e o AMPL foi feita utilizando-se o AMPL API. Foram realizados testes com os sistemas IEEE de 14, 30, 57 e 118 barras e os resultados indicam que a metodologia proposta é capaz de encontrar soluções de muito boa qualidade para o problema. / Abstract: In this work, a new specialized metaheuristic based on the Dynamic Search Fireworks Algorithm with Covariance Mutation (DSFWACM) is applied on the Optimal Power Flow (OPF) problem in transmission systems. In the proposed method, generator bus voltage magnitudes and active power generation are considered as continuous variables and the operating state of the shunts and transformer taps settings are considered as discrete variables. Thus, the model is a Mixed-Integer Nonlinear Programming (MINLP) problem. The adopted resolution strategy is to control, in each iteration, the value of the discrete control variables using the DSFWACM metaheuristic and from the metaheuristic’s chosen values, solve the Nonlinear Programming (NLP) problem that provides the values of the continuous control variables along with the system’s operation state. The DSFWACM metaheuristic was written in MATLAB and the problem model in AMPL. The NLP sub-problems were solved using the KNITRO solver, and the interface between MATLAB and AMPL was implemented using the AMPL API. Tests were conducted with the IEEE 14, 30, 57 and 118-bus systems and the results show that the proposed method is able to find high quality solutions to the problem. / Mestre

This master thesis investigates the integration of sustainability and resilience principles into the design of a distribution supply chain network for copper mining, using a case study at Copperstone Resources AB. The aim is to demonstrate how these considerations can be effectively implemented in the copper mining industry, an area where such integration is largely unexplored. Using a case study approach, an optimization model and sensitivity analysis were developed, resulting in four alternative supply chain network designs: two proposed by the company and two generated by the optimization model. Through multi-criteria decision analysis methods, including the analytical hierarchy process and weighted sum method, the alternatives were assessed with input from Copperstone Resources AB. The findings indicate potential cost savings ranging from 200 to 550 MSEK across the four alternatives over 10 years. The preferred option identified by the analysis involves intermodal transport utilizing electric trucks, railways, and ships to transport copper concentrate to Skelleftehamn and iron concentrate to Amsterdam, Rotterdam, and Antwerp. This alternative is deemed the most efficient, environmentally friendly, and resilient, making it the recommended distribution supply chain network design. It is projected to emit between 25 872 and 81 545 tonnes of CO2 over 10 years, with an estimated investment and operating expense of approximately 2.57 BSEK over the same period. This research contributes to the scientific understanding of integrating sustainability and resilience in supply chain network design, particularly in the copper mining industry. The thesis provides insights for practitioners seeking to optimize their distribution networks while considering environmental and resilience factors.