446 resultados para Expansion Planning
Resumo:
This report was submitted to the Financial Planning Association and is confined to the proposals in relation to compliance with the Best Interests duty (Part B) and the provision of Scaled Advice (Part C) in the FPA Consultation Paper, Modifications to the FPA Code of Professional Practice to incorporate FoFA, released in October 2012.
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The aim of this paper is to implement a Game-Theory based offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. The goal of this work is then to develop a Multi-Objective (MO) optimisation tool able to provide a set of optimal solutions for the inspection task, given the environment data, the mission requirements and the definition of the objectives to minimise. Results indicate the robustness and capability of the method to find the trade-off between the Pareto-optimal solutions.
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This paper presents a novel evolutionary computation approach to three-dimensional path planning for unmanned aerial vehicles (UAVs) with tactical and kinematic constraints. A genetic algorithm (GA) is modified and extended for path planning. Two GAs are seeded at the initial and final positions with a common objective to minimise their distance apart under given UAV constraints. This is accomplished by the synchronous optimisation of subsequent control vectors. The proposed evolutionary computation approach is called synchronous genetic algorithm (SGA). The sequence of control vectors generated by the SGA constitutes to a near-optimal path plan. The resulting path plan exhibits no discontinuity when transitioning from curve to straight trajectories. Experiments and results show that the paths generated by the SGA are within 2% of the optimal solution. Such a path planner when implemented on a hardware accelerator, such as field programmable gate array chips, can be used in the UAV as on-board replanner, as well as in ground station systems for assisting in high precision planning and modelling of mission scenarios.
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Ocean gliders constitute an important advance in the highly demanding ocean monitoring scenario. Their effciency, endurance and increasing robustness make these vehicles an ideal observing platform for many long term oceanographic applications. However, they have proved to be also useful in the opportunis-tic short term characterization of dynamic structures. Among these, mesoscale eddies are of particular interest due to the relevance they have in many oceano-graphic processes.
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As the financial planning industry undergoes a series of reforms aimed at increased professionalism and improved quality of advice, financial planner training in Australia and elsewhere has begun to acknowledge the importance of interdisciplinary knowledge bases in informing both curriculum design and professoinal practice (e.g. FPA2009). This paper underscores the importance of the process of financial planning by providing a conceptual analysis of the six step financial planning process using key mechanisms derived from theory and research in cognate disciplines such as psychology and well-being. The paper identifies how these mechanisms may operate to impact client well-being in the financial planning context. The conceptual mapping of th emechanisms to process elements of financial planning is a unique contribution to the financial planning literature and offers a further framework in the armamentarium of researchers interested in pursuing questions around the value of financial planning. The conceptual framework derived from the analysis also adds to the growing body of literature aimed at developing an integrated model of financial planning.
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In this work, the thermal expansion properties of carbon nanotube (CNT)-reinforced nanocomposites with CNT content ranging from 1 to 15 wt% were evaluated using a multi-scale numerical approach, in which the effects of two parameters, i.e., temperature and CNT content, were investigated extensively. For all CNT contents, the obtained results clearly revealed that within a wide low-temperature range (30°C ~ 62°C), thermal contraction is observed, while thermal expansion occurs in a high-temperature range (62°C ~ 120°C). It was found that at any specified CNT content, the thermal expansion properties vary with temperature - as temperature increases, the thermal expansion rate increases linearly. However, at a specified temperature, the absolute value of the thermal expansion rate decreases nonlinearly as the CNT content increases. Moreover, the results provided by the present multi-scale numerical model were in good agreement with those obtained from the corresponding theoretical analyses and experimental measurements in this work, which indicates that this multi-scale numerical approach provides a powerful tool to evaluate the thermal expansion properties of any type of CNT/polymer nanocomposites and therefore promotes the understanding on the thermal behaviors of CNT/polymer nanocomposites for their applications in temperature sensors, nanoelectronics devices, etc.
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Research on Enterprise Resource Planning (ERP) Systems is becoming a well-established research theme in Information Systems (IS) research. Enterprise Resource Planning Systems, given its unique differentiations with other IS applications, have provided an interesting backdrop to test and re-test some of the key and fundamental concepts in IS. While some researchers have tested well-established concepts of technology acceptance, system usage and system success in the context of ERP Systems, others have researched how new paradigms like cloud computing and social media integrate with ERP Systems. Moreover, ERP Systems provided the context for cross disciplinary research such as knowledge management, project management and business process management research. Almost after two-decades since its inception in IS research, this paper provides a critique of 198 papers published on ERP Systems since 2006-2012. We observe patterns on ES research, provide comparisons to past studies and provide future research directions.
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Purpose – The purpose of this paper is to provide a new type of entry mode decision-making model for construction enterprises involved in international business. Design/methodology/approach – A hybrid method combining analytic hierarchy process (AHP) with preference ranking organization method for enrichment evaluations (PROMETHEE) is used to aid entry mode decisions. The AHP is used to decompose the entry mode problem into several dimensions and determine the weight of each criterion. In addition, PROMETHEE method is used to rank candidate entry modes and carry out sensitivity analyses. Findings – The proposed decision-making method is demonstrated to be a suitable approach to resolve the entry mode selection decision problem. Practical implications – The research provides practitioners with a more systematic decision framework and a more precise decision method. Originality/value – The paper sheds light on the further development of entry strategies for international construction markets. It not only introduces a new decision-making model for entry mode decision making, but also provides a conceptual framework with five determinants for a construction company entry mode selection based on the unique properties of the construction industry.
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This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist; therefore, the use of multicriteria decision aid techniques can potentially allow for convergence to trajectory solutions which better reflect overall mission requirements. In that context, additive multiattribute value theory has been applied to optimize trajectories with respect to multiple objectives. A graphical user interface was developed to allow for knowledge capture from a human decision maker (HDM) through simulated decision scenarios. The expert decision data gathered are converted into value functions and corresponding criteria weightings using utility additive theory. The inclusion of preferences elicited from HDM data within an automated decision system allows for the generation of trajectories which more closely represent the candidate HDM decision preferences. This approach has been demonstrated in this paper through simulation using a fixed-wing UAS operating in low-altitude environments.
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This paper is concerned with the optimal path planning and initialization interval of one or two UAVs in presence of a constant wind. The method compares previous literature results on synchronization of UAVs along convex curves, path planning and sampling in 2D and extends it to 3D. This method can be applied to observe gas/particle emissions inside a control volume during sampling loops. The flight pattern is composed of two phases: a start-up interval and a sampling interval which is represented by a semi-circular path. The methods were tested in four complex model test cases in 2D and 3D as well as one simulated real world scenario in 2D and one in 3D.
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In this paper we construct earthwork allocation plans for a linear infrastructure road project. Fuel consumption metrics and an innovative block partitioning and modelling approach are applied to reduce costs. 2D and 3D variants of the problem were compared to see what effect, if any, occurs on solution quality. 3D variants were also considered to see what additional complexities and difficulties occur. The numerical investigation shows a significant improvement and a reduction in fuel consumption as theorised. The proposed solutions differ considerably from plans that were constructed for a distance based metric as commonly used in other approaches. Under certain conditions, 3D problem instances can be solved optimally as 2D problems.
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The main aim of this paper is to describe an adaptive re-planning algorithm based on a RRT and Game Theory to produce an efficient collision free obstacle adaptive Mission Path Planner for Search and Rescue (SAR) missions. This will provide UAV autopilots and flight computers with the capability to autonomously avoid static obstacles and No Fly Zones (NFZs) through dynamic adaptive path replanning. The methods and algorithms produce optimal collision free paths and can be integrated on a decision aid tool and UAV autopilots.