987 resultados para Berth allocation problem


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Phasor Measurement Units (PMUs) optimized allocation allows control, monitoring and accurate operation of electric power distribution systems, improving reliability and service quality. Good quality and considerable results are obtained for transmission systems using fault location techniques based on voltage measurements. Based on these techniques and performing PMUs optimized allocation it is possible to develop an electric power distribution system fault locator, which provides accurate results. The PMUs allocation problem presents combinatorial features related to devices number that can be allocated, and also probably places for allocation. Tabu search algorithm is the proposed technique to carry out PMUs allocation. This technique applied in a 141 buses real-life distribution urban feeder improved significantly the fault location results. © 2004 IEEE.

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Low flexibility and reliability in the operation of radial distribution networks make those systems be constructed with extra equipment as sectionalising switches in order to reconfigure the network, so the operation quality of the network can be improved. Thus, sectionalising switches are used for fault isolation and for configuration management (reconfiguration). Moreover, distribution systems are being impacted by the increasing insertion of distributed generators. Hence, distributed generation became one of the relevant parameters in the evaluation of systems reconfiguration. Distributed generation may affect distribution networks operation in various ways, causing noticeable impacts depending on its location. Thus, the loss allocation problem becomes more important considering the possibility of open access to the distribution networks. In this work, a graphic simulator for distribution networks with reconfiguration and loss allocation functions, is presented. Reconfiguration problem is solved through a heuristic methodology, using a robust power flow algorithm based on the current summation backward-forward technique, considering distributed generation. Four different loss allocation methods (Zbus, Direct Loss Coefficient, Substitution and Marginal Loss Coefficient) are implemented and compared. Results for a 32-bus medium voltage distribution network, are presented and discussed.

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This paper presents a mixed-integer linear programming model to solve the problem of allocating voltage regulators and fixed or switched capacitors (VRCs) in radial distribution systems. The use of a mixed-integer linear model guarantees convergence to optimality using existing optimization software. In the proposed model, the steady-state operation of the radial distribution system is modeled through linear expressions. The results of one test system and one real distribution system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. An heuristic to obtain the Pareto front for the multiobjective VRCs allocation problem is also presented. © 2012 Elsevier Ltd. All rights reserved.

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This work presents exact algorithms for the Resource Allocation and Cyclic Scheduling Problems (RA&CSPs). Cyclic Scheduling Problems arise in a number of application areas, such as in hoist scheduling, mass production, compiler design (implementing scheduling loops on parallel architectures), software pipelining, and in embedded system design. The RA&CS problem concerns time and resource assignment to a set of activities, to be indefinitely repeated, subject to precedence and resource capacity constraints. In this work we present two constraint programming frameworks facing two different types of cyclic problems. In first instance, we consider the disjunctive RA&CSP, where the allocation problem considers unary resources. Instances are described through the Synchronous Data-flow (SDF) Model of Computation. The key problem of finding a maximum-throughput allocation and scheduling of Synchronous Data-Flow graphs onto a multi-core architecture is NP-hard and has been traditionally solved by means of heuristic (incomplete) algorithms. We propose an exact (complete) algorithm for the computation of a maximum-throughput mapping of applications specified as SDFG onto multi-core architectures. Results show that the approach can handle realistic instances in terms of size and complexity. Next, we tackle the Cyclic Resource-Constrained Scheduling Problem (i.e. CRCSP). We propose a Constraint Programming approach based on modular arithmetic: in particular, we introduce a modular precedence constraint and a global cumulative constraint along with their filtering algorithms. Many traditional approaches to cyclic scheduling operate by fixing the period value and then solving a linear problem in a generate-and-test fashion. Conversely, our technique is based on a non-linear model and tackles the problem as a whole: the period value is inferred from the scheduling decisions. The proposed approaches have been tested on a number of non-trivial synthetic instances and on a set of realistic industrial instances achieving good results on practical size problem.

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When project managers determine schedules for resource-constrained projects, they commonly use commercial project management software packages. Which resource-allocation methods are implemented in these packages is proprietary information. The resource-allocation problem is in general computationally difficult to solve to optimality. Hence, the question arises if and how various project management software packages differ in quality with respect to their resource-allocation capabilities. None of the few existing papers on this subject uses a sizeable data set and recent versions of common software packages. We experimentally analyze the resource-allocation capabilities of Acos Plus.1, AdeptTracker Professional, CS Project Professional, Microsoft Office Project 2007, Primavera P6, Sciforma PS8, and Turbo Project Professional. Our analysis is based on 1560 instances of the precedence- and resource-constrained project scheduling problem RCPSP. The experiment shows that using the resource-allocation feature of these packages may lead to a project duration increase of almost 115% above the best known feasible schedule. The increase gets larger with increasing resource scarcity and with increasing number of activities. We investigate the impact of different complexity scenarios and priority rules on the project duration obtained by the software packages. We provide a decision table to support managers in selecting a software package and a priority rule.

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In this work, we propose a distributed rate allocation algorithm that minimizes the average decoding delay for multimedia clients in inter-session network coding systems. We consider a scenario where the users are organized in a mesh network and each user requests the content of one of the available sources. We propose a novel distributed algorithm where network users determine the coding operations and the packet rates to be requested from the parent nodes, such that the decoding delay is minimized for all clients. A rate allocation problem is solved by every user, which seeks the rates that minimize the average decoding delay for its children and for itself. Since this optimization problem is a priori non-convex, we introduce the concept of equivalent packet flows, which permits to estimate the expected number of packets that every user needs to collect for decoding. We then decompose our original rate allocation problem into a set of convex subproblems, which are eventually combined to obtain an effective approximate solution to the delay minimization problem. The results demonstrate that the proposed scheme eliminates the bottlenecks and reduces the decoding delay experienced by users with limited bandwidth resources. We validate the performance of our distributed rate allocation algorithm in different video streaming scenarios using the NS-3 network simulator. We show that our system is able to take benefit of inter-session network coding for simultaneous delivery of video sessions in networks with path diversity.

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Resource allocation is one of the major decision problems arising in higher education. Resources must be allocated optimally in such a way that the performance of universities can be improved. This paper applies an integrated multiple criteria decision making approach to the resource allocation problem. In the approach, the Analytic Hierarchy Process (AHP) is first used to determine the priority or relative importance of proposed projects with respect to the goals of the universities. Then, the Goal Programming (GP) model incorporating the constraints of AHP priority, system, and resource is formulated for selecting the best set of projects without exceeding the limited available resources. The projects include 'hardware' (tangible university's infrastructures), and 'software' (intangible effects that can be beneficial to the university, its members, and its students). In this paper, two commercial packages are used: Expert Choice for determining the AHP priority ranking of the projects, and LINDO for solving the GP model. Copyright © 2007 Inderscience Enterprises Ltd.

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Allocation procedures, have attracted considerable interest among higher education institutions in recent years. Relevant previous research indicates that several universities adopt different approaches to the resource allocation problem, employing models and procedures that reflect their organisational arrangements and their internal socio – political dynamics. We argue that while studying accounting processes in their organisational context, the role of trust should also be considered carefully. In particular, it is very important to consider the attitudes of the individuals involved and interacting within organisational processes, and especially the trust between them, which plays an important role to the overall good governance of these processes. In our study, the role of interpersonal trust in an old Scottish University resource allocation process is examined. The study indicates that trust is a very necessary insight to the facilitation of social structures of accountability that enhance a better governance of the resource allocation process.

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Social network sites (SNS), such as Facebook, Google+ and Twitter, have attracted hundreds of millions of users daily since their appearance. Within SNS, users connect to each other, express their identity, disseminate information and form cooperation by interacting with their connected peers. The increasing popularity and ubiquity of SNS usage and the invaluable user behaviors and connections give birth to many applications and business models. We look into several important problems within the social network ecosystem. The first one is the SNS advertisement allocation problem. The other two are related to trust mechanisms design in social network setting, including local trust inference and global trust evaluation. In SNS advertising, we study the problem of advertisement allocation from the ad platform's angle, and discuss its differences with the advertising model in the search engine setting. By leveraging the connection between social networks and hyperbolic geometry, we propose to solve the problem via approximation using hyperbolic embedding and convex optimization. A hyperbolic embedding method, \hcm, is designed for the SNS ad allocation problem, and several components are introduced to realize the optimization formulation. We show the advantages of our new approach in solving the problem compared to the baseline integer programming (IP) formulation. In studying the problem of trust mechanisms in social networks, we consider the existence of distrust (i.e. negative trust) relationships, and differentiate between the concept of local trust and global trust in social network setting. In the problem of local trust inference, we propose a 2-D trust model. Based on the model, we develop a semiring-based trust inference framework. In global trust evaluation, we consider a general setting with conflicting opinions, and propose a consensus-based approach to solve the complex problem in signed trust networks.

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Tese de Doutoramento em Engenharia Civil.

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We consider the following allocation problem: A fixed number of public facilities must be located on a line. Society is composed of $N$ agents, who must be allocated to one and only one of these facilities. Agents have single peaked preferences over the possible location of the facilities they are assigned to, and do not care about the location of the rest of facilities. There is no congestion. In this context, we observe that if a public decision is a Condorcet winner, then it satisfies nice properties of internal and external stability. Though in many contexts and for some preference profiles there may be no Condorcet winners, we study the extent to which stability can be made compatible with the requirement of choosing Condorcet winners whenever they exist.

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Pontryagin's maximum principle from optimal control theory is used to find the optimal allocation of energy between growth and reproduction when lifespan may be finite and the trade-off between growth and reproduction is linear. Analyses of the optimal allocation problem to date have generally yielded bang-bang solutions, i.e. determinate growth: life-histories in which growth is followed by reproduction, with no intermediate phase of simultaneous reproduction and growth. Here we show that an intermediate strategy (indeterminate growth) can be selected for if the rates of production and mortality either both increase or both decrease with increasing body size, this arises as a singular solution to the problem. Our conclusion is that indeterminate growth is optimal in more cases than was previously realized. The relevance of our results to natural situations is discussed.

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La présente contribution examine les fondements normatifs ainsi que les implications éthiques du droit à l’eau, tel qu’il fut reconnu en 2002 par le comité onusien des droits économiques, sociaux et culturels. Il sera défendu que le droit à l’eau potable peut être justifié en tant que droit moral fondamental, de par son caractère indispensable en vue de la garantie des conditions basiques de survie. Cet état de fait, cependant, s’avère moins évident au vue d’un droit à l’eau d’usage non-domestique. Ici, la discussion se rapproche des débats accompagnant le concept beaucoup plus complexe des droits sociaux et économiques. Par rapport à ce groupe de droits, la question de l’allocation est des plus controversées: à qui incombe-t-il de garantir leur respect? Dans le but d’éviter cette problématique d’allocation, le présent essai soulèvera la question de savoir, si la limitation de l’accès à l’eau peut être conçue comme une violation d’autres droits moraux: bien qu’il y ait des cas où des entreprises transnationales déploient des activités nuisibles à l’égard des populations pauvres en polluant sciemment leurs ressources en eau ou en initiant et en exécutant des stratégies de privatisation les privant de leurs droits, la crise globale de l’eau ne saura être rattachée uniquement aux effets de la mondialisation. Plutôt, l’on reconnaîtra la nécessité d’efforts positifs et soutenus de la part des pays développés en vue de la réalisation d’un approvisionnement suffisant en eau pour tous.

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We present an optimal methodology for synchronized scheduling of production assembly with air transportation to achieve accurate delivery with minimized cost in consumer electronics supply chain (CESC). This problem was motivated by a major PC manufacturer in consumer electronics industry, where it is required to schedule the delivery requirements to meet the customer needs in different parts of South East Asia. The overall problem is decomposed into two sub-problems which consist of an air transportation allocation problem and an assembly scheduling problem. The air transportation allocation problem is formulated as a Linear Programming Problem with earliness tardiness penalties for job orders. For the assembly scheduling problem, it is basically required to sequence the job orders on the assembly stations to minimize their waiting times before they are shipped by flights to their destinations. Hence the second sub-problem is modelled as a scheduling problem with earliness penalties. The earliness penalties are assumed to be independent of the job orders.

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Pontryagin's maximum principle from optimal control theory is used to find the optimal allocation of energy between growth and reproduction when lifespan may be finite and the trade-off between growth and reproduction is linear. Analyses of the optimal allocation problem to date have generally yielded bang-bang solutions, i.e. determinate growth: life-histories in which growth is followed by reproduction, with no intermediate phase of simultaneous reproduction and growth. Here we show that an intermediate strategy (indeterminate growth) can be selected for if the rates of production and mortality either both increase or both decrease with increasing body size, this arises as a singular solution to the problem. Our conclusion is that indeterminate growth is optimal in more cases than was previously realized. The relevance of our results to natural situations is discussed.