953 resultados para Distribution system optimization
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We consider the two-level network design problem with intermediate facilities. This problem consists of designing a minimum cost network respecting some requirements, usually described in terms of the network topology or in terms of a desired flow of commodities between source and destination vertices. Each selected link must receive one of two types of edge facilities and the connection of different edge facilities requires a costly and capacitated vertex facility. We propose a hybrid decomposition approach which heuristically obtains tentative solutions for the vertex facilities number and location and use these solutions to limit the computational burden of a branch-and-cut algorithm. We test our method on instances of the power system secondary distribution network design problem. The results show that the method is efficient both in terms of solution quality and computational times. (C) 2010 Elsevier Ltd. All rights reserved.
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This thesis is done to solve two issues for Sayid Paper Mill Ltd Pakistan. Section one deals with a practical problem arise in SPM that is cutting a given set of raw paper rolls of known length and width, and a set of product paper rolls of known length (equal to the length of raw paper rolls) and width, practical cutting constraints on a single cutting machine, according to demand orders for all customers. To solve this problem requires to determine an optimal cutting schedule to maximize the overall cutting process profitability while satisfying all demands and cutting constraints. The aim of this part of thesis is to develop a mathematical model which solves this problem.Second section deals with a problem of delivering final product from warehouse to different destinations by finding shortest paths. It is an operational routing problem to decide the daily routes for sending trucks to different destination to deliver their final product. This industrial problem is difficult and includes aspect such as delivery to a single destination and multiple destinations with limited resources. The aim of this part of thesis is to develop a process which helps finding shortest path.
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This Thesis project is a part of the research conducted in Solar industry. ABSOLICON Solar Concentrator AB has invented and started production of the prospective solar concentrated system Absolicon X10. The aims of this Thesis project are designing, assembling, calibrating and putting in operation the automatic measurement system intended to evaluate distribution of density of solar radiation in the focal line of the concentrated parabolic reflectors and to measure radiation from the artificial source of light being a calibration-testing tool.On the basis of the requirements of the company’s administration and needs of designing the concentrated reflectors the operation conditions for the Sun-Walker were formulated. As the first step, the complex design of the whole system was made and division on the parts was specified. After the preliminary conducted simulation of the functions and operation conditions of the all parts were formulated.As the next steps, the detailed design of all the parts was made. Most components were ordered from respective companies. Some of the mechanical components were made in the workshop of the company. All parts of the Sun-Walker were assembled and tested. The software part, which controls the Sun-Walker work and conducts measurements of solar irradiation, was created on the LabVIEW basis. To tune and test the software part, the special simulator was designed and assembled.When all parts were assembled in the complete system, the Sun-Walker was tested, calibrated and tuned.
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This thesis contributes to the heuristic optimization of the p-median problem and Swedish population redistribution. The p-median model is the most representative model in the location analysis. When facilities are located to a population geographically distributed in Q demand points, the p-median model systematically considers all the demand points such that each demand point will have an effect on the decision of the location. However, a series of questions arise. How do we measure the distances? Does the number of facilities to be located have a strong impact on the result? What scale of the network is suitable? How good is our solution? We have scrutinized a lot of issues like those. The reason why we are interested in those questions is that there are a lot of uncertainties in the solutions. We cannot guarantee our solution is good enough for making decisions. The technique of heuristic optimization is formulated in the thesis. Swedish population redistribution is examined by a spatio-temporal covariance model. A descriptive analysis is not always enough to describe the moving effects from the neighbouring population. A correlation or a covariance analysis is more explicit to show the tendencies. Similarly, the optimization technique of the parameter estimation is required and is executed in the frame of statistical modeling.
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Drinking water distribution networks risk exposure to malicious or accidental contamination. Several levels of responses are conceivable. One of them consists to install a sensor network to monitor the system on real time. Once a contamination has been detected, this is also important to take appropriate counter-measures. In the SMaRT-OnlineWDN project, this relies on modeling to predict both hydraulics and water quality. An online model use makes identification of the contaminant source and simulation of the contaminated area possible. The objective of this paper is to present SMaRT-OnlineWDN experience and research results for hydraulic state estimation with sampling frequency of few minutes. A least squares problem with bound constraints is formulated to adjust demand class coefficient to best fit the observed values at a given time. The criterion is a Huber function to limit the influence of outliers. A Tikhonov regularization is introduced for consideration of prior information on the parameter vector. Then the Levenberg-Marquardt algorithm is applied that use derivative information for limiting the number of iterations. Confidence intervals for the state prediction are also given. The results are presented and discussed on real networks in France and Germany.
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An underwater gas pipeline is the portion of the pipeline that crosses a river beneath its bottom. Underwater gas pipelines are subject to increasing dangers as time goes by. An accident at an underwater gas pipeline can lead to technological and environmental disaster on the scale of an entire region. Therefore, timely troubleshooting of all underwater gas pipelines in order to prevent any potential accidents will remain a pressing task for the industry. The most important aspect of resolving this challenge is the quality of the automated system in question. Now the industry doesn't have any automated system that fully meets the needs of the experts working in the field maintaining underwater gas pipelines. Principle Aim of this Research: This work aims to develop a new system of automated monitoring which would simplify the process of evaluating the technical condition and decision making on planning and preventive maintenance and repair work on the underwater gas pipeline. Objectives: Creation a shared model for a new, automated system via IDEF3; Development of a new database system which would store all information about underwater gas pipelines; Development a new application that works with database servers, and provides an explanation of the results obtained from the server; Calculation of the values MTBF for specified pipelines based on quantitative data obtained from tests of this system. Conclusion: The new, automated system PodvodGazExpert has been developed for timely and qualitative determination of the physical conditions of underwater gas pipeline; The basis of the mathematical analysis of this new, automated system uses principal component analysis method; The process of determining the physical condition of an underwater gas pipeline with this new, automated system increases the MTBF by a factor of 8.18 above the existing system used today in the industry.
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This paper describes the formulation of a Multi-objective Pipe Smoothing Genetic Algorithm (MOPSGA) and its application to the least cost water distribution network design problem. Evolutionary Algorithms have been widely utilised for the optimisation of both theoretical and real-world non-linear optimisation problems, including water system design and maintenance problems. In this work we present a pipe smoothing based approach to the creation and mutation of chromosomes which utilises engineering expertise with the view to increasing the performance of the algorithm whilst promoting engineering feasibility within the population of solutions. MOPSGA is based upon the standard Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and incorporates a modified population initialiser and mutation operator which directly targets elements of a network with the aim to increase network smoothness (in terms of progression from one diameter to the next) using network element awareness and an elementary heuristic. The pipe smoothing heuristic used in this algorithm is based upon a fundamental principle employed by water system engineers when designing water distribution pipe networks where the diameter of any pipe is never greater than the sum of the diameters of the pipes directly upstream resulting in the transition from large to small diameters from source to the extremities of the network. MOPSGA is assessed on a number of water distribution network benchmarks from the literature including some real-world based, large scale systems. The performance of MOPSGA is directly compared to that of NSGA-II with regard to solution quality, engineering feasibility (network smoothness) and computational efficiency. MOPSGA is shown to promote both engineering and hydraulic feasibility whilst attaining good infrastructure costs compared to NSGA-II.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Algumas culturas têm pouca adaptação ao sistema plantio direto (SPD), em vista da alta compactação da camada superficial do solo. Nesse caso, o mecanismo utilizado na semeadora para a abertura dos sulcos para deposição do fertilizante pode ter grande importância no sentido de facilitar a penetração das raízes. Avaliouse a influência do mecanismo de distribuição de fertilizante e da adubação nitrogenada na cultura do arroz de terras altas (Oryza sativa) no sistema plantio direto. O experimento foi conduzido nos anos agrícolas 2001/2002 e 2002/2003, em Botucatu-SP, Brasil. O delineamento experimental foi em blocos casualizados, com parcelas subdivididas e quatro repetições. As parcelas foram constituídas por dois mecanismos de distribuição de fertilizantes (haste sulcadora e disco duplo). Nas subparcelas, quatro níveis de N foram aplicados em cobertura (0, 40, 80 e 120 kg ha-1). Avaliou-se a profundidade de abertura do sulco e de deposição das sementes, a população de plantas, a altura de plantas, o número de colmos e de panículas m-2, o número total de espiguetas por panícula, a fertilidade das espiguetas, a massa de 1.000 grãos, a matéria seca da parte aérea, a produtividade e o teor de N na folha bandeira. O sucesso no estabelecimento da cultura do arroz de terras altas no SPD nas regiões de inverno seco do Brasil está diretamente ligado ao mecanismo de distribuição das semeadoras-adubadoras. A haste sulcadora promoveu maior profundidade de deposição de sementes, conseqüentemente reduzindo o estande, o número de panículas por área e a produtividade. A aplicação de N em cobertura no arroz de terras altas em SPD proporciona maiores produtividades quando a semeadura é realizada com mecanismo de disco duplo.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Markovian algorithms for estimating the global maximum or minimum of real valued functions defined on some domain Omega subset of R-d are presented. Conditions on the search schemes that preserve the asymptotic distribution are derived. Global and local search schemes satisfying these conditions are analysed and shown to yield sharper confidence intervals when compared to the i.i.d. case.
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The ability of neural networks to realize some complex nonlinear function makes them attractive for system identification. This paper describes a novel method using artificial neural networks to solve robust parameter estimation problems for nonlinear models with unknown-but-bounded errors and uncertainties. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach.
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In the present study, a single procedure was established to investigate the effect of the spatial distribution of immatures in patchy resources, on the outcome of larval competition for food. in experimental populations of Chrysomya megacephala. A theoretical model of intraspecific competition was extended and applied to experimental data on survival to adulthood for 20 larval densities, to obtain the theoretical mean number of individuals that will survive, considering a hypothetical previous random adult oviposition in a system of homogeneous patches. The survival curve obtained suggests that the larval competition for food in C. megacephala is of the scramble/exploitative type, which corroborates results from previous studies, although the latter did not consider the correlation between local and global abundances. The present model allows that experimental data could be perfectly applicable, and it incorporates fundamental assumptions about the spatial context of competition for patchy resources in blowflies, and may be applied to the optimization of mass rearing techniques and to the maintenance of insect colonies under experimental conditions.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)