883 resultados para effort allocation


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To allocate and size capacitors in a distribution system, an optimization algorithm, called Discrete Particle Swarm Optimization (DPSO), is employed in this paper. The objective is to minimize the transmission line loss cost plus capacitors cost. During the optimization procedure, the bus voltage, the feeder current and the reactive power flowing back to the source side should be maintained within standard levels. To validate the proposed method, the semi-urban distribution system that is connected to bus 2 of the Roy Billinton Test System (RBTS) is used. This 37-bus distribution system has 22 loads being located in the secondary side of a distribution substation (33/11 kV). Reducing the transmission line loss in a standard system, in which the transmission line loss consists of only about 6.6 percent of total power, the capabilities of the proposed technique are seen to be validated.

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In this paper, the placement and sizing of Distributed Generators (DG) in distribution networks are determined optimally. The objective is to minimize the loss and to improve the reliability. The constraints are the bus voltage, feeder current and the reactive power flowing back to the source side. The placement and size of DGs are optimized using a combination of Discrete Particle Swarm Optimization (DPSO) and Genetic Algorithm (GA). This increases the diversity of the optimizing variables in DPSO not to be stuck in the local minima. To evaluate the proposed algorithm, the semi-urban 37-bus distribution system connected at bus 2 of the Roy Billinton Test System (RBTS), which is located at the secondary side of a 33/11 kV distribution substation, is used. The results finally illustrate the efficiency of the proposed method.

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The focus of this thesis is discretionary work effort, that is, work effort that is voluntary, is above and beyond what is minimally required or normally expected to avoid reprimand or dismissal, and is organisationally functional. Discretionary work effort is an important construct because it is known to affect individual performance as well as organisational efficiency and effectiveness. To optimise organisational performance and ensure their long term competitiveness and sustainability, firms need to be able to induce their employees to work at or near their peak level. To work at or near their peak level, individuals must be willing to supply discretionary work effort. Thus, managers need to understand the determinants of discretionary work effort. Nonetheless, despite many years of scholarly investigation across multiple disciplines, considerable debate still exists concerning why some individuals supply only minimal work effort whilst others expend effort well above and beyond what is minimally required of them (Le. they supply discretionary work effort). Even though it is well recognised that discretionary work effort is important for promoting organisational performance and effectiveness, many authors claim that too little is being done by managers to increase the discretionary work effort of their employees. In this research, I have adopted a multi-disciplinary approach towards investigating the role of monetary and non-monetary work environment characteristics in determining discretionary work effort. My central research questions were "What non-monetary work environment characteristics do employees perceive as perks (perquisites) and irks (irksome work environment characteristics)?" and "How do perks, irks and monetary rewards relate to an employee's level of discretionary work effort?" My research took a unique approach in addressing these research questions. By bringing together the economics and organisational behaviour (OB) literatures, I identified problems with the current definition and conceptualisations of the discretionary work effort construct. I then developed and empirically tested a more concise and theoretically-based definition and conceptualisation of this construct. In doing so, I disaggregated discretionary work effort to include three facets - time, intensity and direction - and empirically assessed if different classes of work environment characteristics have a differential pattern of relationships with these facets. This analysis involved a new application of a multi-disciplinary framework of human behaviour as a tool for classifying work environment characteristics and the facets of discretionary work effort. To test my model of discretionary work effort, I used a public sector context in which there has been limited systematic empirical research into work motivation. The program of research undertaken involved three separate but interrelated studies using mixed methods. Data on perks, irks, monetary rewards and discretionary work effort were gathered from employees in 12 organisations in the local government sector in Western Australia. Non-monetary work environment characteristics that should be associated with discretionary work effort were initially identified through a review of the literature. Then, a qualitative study explored what work behaviours public sector employees perceive as discretionary and what perks and irks were associated with high and low levels of discretionary work effort. Next, a quantitative study developed measures of these perks and irks. A Q-sorttype procedure and exploratory factor analysis were used to develop the perks and irks measures. Finally, a second quantitative study tested the relationships amongst perks, irks, monetary rewards and discretionary work effort. Confirmatory factor analysis was firstly used to confirm the factor structure of the measurement models. Correlation analysis, regression analysis and effect-size correlation analysis were used to test the hypothesised relationships in the proposed model of discretionary work effort. The findings confirmed five hypothesised non-monetary work environment characteristics as common perks and two of three hypothesised non-monetary work environment characteristics as common irks. Importantly, they showed that perks, irks and monetary rewards are differentially related to the different facets of discretionary work effort. The convergent and discriminant validities of the perks and irks constructs as well as the time, intensity and direction facets of discretionary work effort were generally confirmed by the research findings. This research advances the literature in several ways: (i) it draws on the Economics and OB literatures to redefine and reconceptualise the discretionary work effort construct to provide greater definitional clarity and a more complete conceptualisation of this important construct; (ii) it builds on prior research to create a more comprehensive set of perks and irks for which measures are developed; (iii) it develops and empirically tests a new motivational model of discretionary work effort that enhances our understanding of the nature and functioning of perks and irks and advances our ability to predict discretionary work effort; and (iv) it fills a substantial gap in the literature on public sector work motivation by revealing what work behaviours public sector employees perceive as discretionary and what work environment characteristics are associated with their supply of discretionary work effort. Importantly, by disaggregating discretionary work effort this research provides greater detail on how perks, irks and monetary rewards are related to the different facets of discretionary work effort. Thus, from a theoretical perspective this research also demonstrates the conceptual meaningfulness and empirical utility of investigating the different facets of discretionary work effort separately. From a practical perspective, identifying work environment factors that are associated with discretionary work effort enhances managers' capacity to tap this valuable resource. This research indicates that to maximise the potential of their human resources, managers need to address perks, irks and monetary rewards. It suggests three different mechanisms through which managers might influence discretionary work effort and points to the importance of training for both managers and non-managers in cultivating positive interpersonal relationships.

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Lifecycle funds offered by retirement plan providers allocate aggressively to risky asset classes when the employee participants are young, gradually switching to more conservative asset classes as they grow older and approach retirement. This approach focuses on maximizing growth of the accumulation fund in the initial years and preserving its value in the later years. The authors simulate terminal wealth outcomes based on conventional lifecycle asset allocation rules as well as on contrarian strategies that reverse the direction of asset switching. The evidence suggests that the growth in portfolio size over time significantly impacts the asset allocation decision. Due to the portfolio size effect that is observed by the authors, the terminal value of accumulation in retirement accounts is influenced more by the asset allocation strategy adopted in later years relative to that adopted in early years. By mechanistically switching to conservative assets in the later years of a plan, lifecycle strategies sacrifice significant growth opportunity and prove counterproductive to the participant's wealth accumulation objective. The authors' conclude that this sacrifice does not seem to be compensated adequately in terms of reducing the risk of potentially adverse outcomes.

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In this paper, the optimal allocation and sizing of distributed generators (DGs) in a distribution system is studied. To achieve this goal, an optimization problem should be solved in which the main objective is to minimize the DGs cost and to maximise the reliability simultaneously. The active power balance between loads and DGs during the isolation time is used as a constraint. Another point considered in this process is the load shedding. It means that if the summation of DGs active power in a zone, isolated by the sectionalizers because of a fault, is less than the total active power of loads located in that zone, the program start shedding the loads in one-by-one using the priority rule still the active power balance is satisfied. This assumption decreases the reliability index, SAIDI, compared with the case loads in a zone are shed when total DGs power is less than the total load power. To validate the proposed method, a 17-bus distribution system is employed and the results are analysed.

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Distributed Denial of Services DDoS, attacks has become one of the biggest threats for resources over Internet. Purpose of these attacks is to make servers deny from providing services to legitimate users. These attacks are also used for occupying media bandwidth. Currently intrusion detection systems can just detect the attacks but cannot prevent / track the location of intruders. Some schemes also prevent the attacks by simply discarding attack packets, which saves victim from attack, but still network bandwidth is wasted. In our opinion, DDoS requires a distributed solution to save wastage of resources. The paper, presents a system that helps us not only in detecting such attacks but also helps in tracing and blocking (to save the bandwidth as well) the multiple intruders using Intelligent Software Agents. The system gives dynamic response and can be integrated with the existing network defense systems without disturbing existing Internet model. We have implemented an agent based networking monitoring system in this regard.

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In cloud computing resource allocation and scheduling of multiple composite web services is an important challenge. This is especially so in a hybrid cloud where there may be some free resources available from private clouds but some fee-paying resources from public clouds. Meeting this challenge involves two classical computational problems. One is assigning resources to each of the tasks in the composite web service. The other is scheduling the allocated resources when each resource may be used by more than one task and may be needed at different points of time. In addition, we must consider Quality-of-Service issues, such as execution time and running costs. Existing approaches to resource allocation and scheduling in public clouds and grid computing are not applicable to this new problem. This paper presents a random-key genetic algorithm that solves new resource allocation and scheduling problem. Experimental results demonstrate the effectiveness and scalability of the algorithm.

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In open railway access markets, a train service provider (TSP) negotiates with an infrastructure provider (IP) for track access rights. This negotiation has been modeled by a multi-agent system (MAS) in which the IP and TSP are represented by separate software agents. One task of the IP agent is to generate feasible (and preferably optimal) track access rights, subject to the constraints submitted by the TSP agent. This paper formulates an IP-TSP transaction and proposes a branch-and-bound algorithm for the IP agent to identify the optimal track access rights. Empirical simulation results show that the model is able to emulate rational agent behaviors. The simulation results also show good consistency between timetables attained from the proposed methods and those derived by the scheduling principles adopted in practice.

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This paper explores the conditions of acceptability of differing allocation systems under scarcity and evaluates what makes a price system more or less fair. We find that fairness in an allocation arrangement depend on the institutional settings inherent in the situation, such as information, transparency and competition and the perceived institutional quality e.g., fiscal exchange and institutional trust). Results also indicate that the solution “weak people first” is seen as the fairest approach to an excess demand situation, followed by “first come, first serve”, the price system and an auction system. On the other hand, a random procedure or an allocation through the government is not perceived to be fair. Moreover, economics students seemed to be less sceptical towards the price system than other subjects although we observe that female students are more sceptical than male students.

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A substantial body of research is focused on understanding the relationships between socio-demographics, land-use characteristics, and mode specific attributes on travel mode choice and time-use patterns. Residential and commercial densities, inter-mixing of land uses, and route directness in conjunction with transportation performance characteristics interact to influence accessibility to destinations as well as time spent traveling and engaging in activities. This study uniquely examines the activity durations undertaken for out-of-home subsistence; maintenance, and discretionary activities. Also examined are total tour durations (summing all activity categories within a tour). Cross-sectional activities are obtained from household activity travel survey data from the Atlanta Metropolitan Region. Time durations allocated to weekdays and weekends are compared. The censoring and endogeneity between activity categories and within individuals are captured using multiple equations Tobit models. The analysis and modeling reveal that land-use characteristics such as net residential density and the number of commercial parcels within a kilometer of a residence are associated with differences in weekday and weekend time-use allocations. Household type and structure are significant predictors across the three activity categories, but not for overall travel times. Tour characteristics such as time-of-day and primary travel mode of the tours also affect traveler's out-of-home activity-tour time-use patterns.

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Robustness of the track allocation problem is rarely addressed in literatures and the obtained track allocation schemes (TAS) embody some bottlenecks. Therefore, an approach to detect bottlenecks is needed to support local optimization. First a TAS is transformed to an executable model by Petri nets. Then disturbances analysis is performed using the model and the indicators of the total trains' departure delays are collected to detect bottlenecks when each train suffers a disturbance. Finally, the results of the tests based on a rail hub linking six lines and a TAS about thirty minutes show that the minimum buffer time is 21 seconds and there are two bottlenecks where the buffer times are 57 and 44 seconds respectively, and it indicates that the bottlenecks do not certainly locate at the area where there is minimum buffer time. The proposed approach can further support selection of multi schemes and robustness optimization.