952 resultados para optimal growth strategy
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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.
Resumo:
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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Designing an efficient sampling strategy is of crucial importance for habitat suitability modelling. This paper compares four such strategies, namely, 'random', 'regular', 'proportional-stratified' and 'equal -stratified'- to investigate (1) how they affect prediction accuracy and (2) how sensitive they are to sample size. In order to compare them, a virtual species approach (Ecol. Model. 145 (2001) 111) in a real landscape, based on reliable data, was chosen. The distribution of the virtual species was sampled 300 times using each of the four strategies in four sample sizes. The sampled data were then fed into a GLM to make two types of prediction: (1) habitat suitability and (2) presence/ absence. Comparing the predictions to the known distribution of the virtual species allows model accuracy to be assessed. Habitat suitability predictions were assessed by Pearson's correlation coefficient and presence/absence predictions by Cohen's K agreement coefficient. The results show the 'regular' and 'equal-stratified' sampling strategies to be the most accurate and most robust. We propose the following characteristics to improve sample design: (1) increase sample size, (2) prefer systematic to random sampling and (3) include environmental information in the design'
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Even though patients who develop ischemic stroke despite taking antiplatelet drugs represent a considerable proportion of stroke hospital admissions, there is a paucity of data from investigational studies regarding the most suitable therapeutic intervention. There have been no clinical trials to test whether increasing the dose or switching antiplatelet agents reduces the risk for subsequent events. Certain issues have to be considered in patients managed for a first or recurrent stroke while receiving antiplatelet agents. Therapeutic failure may be due to either poor adherence to treatment, associated co-morbid conditions and diminished antiplatelet effects (resistance to treatment). A diagnostic work up is warranted to identify the etiology and underlying mechanism of stroke, thereby guiding further management. Risk factors (including hypertension, dyslipidemia and diabetes) should be treated according to current guidelines. Aspirin or aspirin plus clopidogrel may be used in the acute and early phase of ischemic stroke, whereas in the long-term, antiplatelet treatment should be continued with aspirin, aspirin/extended release dipyridamole or clopidogrel monotherapy taking into account tolerance, safety, adherence and cost issues. Secondary measures to educate patients about stroke, the importance of adherence to medication, behavioral modification relating to tobacco use, physical activity, alcohol consumption and diet to control excess weight should also be implemented.
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In this Master’s thesis agent-based modeling has been used to analyze maintenance strategy related phenomena. The main research question that has been answered was: what does the agent-based model made for this study tell us about how different maintenance strategy decisions affect profitability of equipment owners and maintenance service providers? Thus, the main outcome of this study is an analysis of how profitability can be increased in industrial maintenance context. To answer that question, first, a literature review of maintenance strategy, agent-based modeling and maintenance modeling and optimization was conducted. This review provided the basis for making the agent-based model. Making the model followed a standard simulation modeling procedure. With the simulation results from the agent-based model the research question was answered. Specifically, the results of the modeling and this study are: (1) optimizing the point in which a machine is maintained increases profitability for the owner of the machine and also the maintainer with certain conditions; (2) time-based pricing of maintenance services leads to a zero-sum game between the parties; (3) value-based pricing of maintenance services leads to a win-win game between the parties, if the owners of the machines share a substantial amount of their value to the maintainers; and (4) error in machine condition measurement is a critical parameter to optimizing maintenance strategy, and there is real systemic value in having more accurate machine condition measurement systems.
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Tämän tutkimuksen tarkoituksena oli tunnistaa uusia markkinoita ja markkinasegmenttejä yrityksen kasvustrategiaa varten. Yritys on kasvanut erittäin voimakkaasti viime vuosina nykyisillä markkinoillaan ja haluaa nyt jatkaa kasvuaan uusilla markkinoilla. Työ koostuu kirjallisuuskatsauksesta ja empiirisestä osuudesta. Kirjallisuuskatsauksessa on tunnistettu useita pk-yrityksen kasvuun vaikuttavia tekijöitä, uusien markkinoiden kartoittamiseen ja arvioimiseen vaikuttavia tekijöitä, ja lisäksi liiketoimintastrategiaan ja markkinasegmentin valintaan vaikuttavia tekijöitä. Empiirisen osuuden data kerättiin 60 asiantuntijahaastattelusta, joilla kartoitettiin kokonaismarkkinoita ja saatiin tarkkaa markkinainformaatiota kohdemarkkinoista. Tutkimuksessa tunnistettiin kymmenen potentiaalista toimialaa ja 54 potentiaalista markkinasegmenttiä. Kirjallisuudesta tunnistetuilla kriteereillä, teknologisin perustein ja yrityksen omien näkökulmien perusteella näistä valittiin kohdemarkkinoiksi kahdeksan. Tutkimuksessa kehitettiin markkinasegmenttien arviointiin malli. Mallin avulla valitut kahdeksan markkinasegmenttiä listattiin järjestykseen niiden houkuttelevuuden perusteella. Jatkotoimenpiteenä yrityksessä tullaan kehittämään kasvustrategia perustuen tutkimuksen tuloksille.
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The top managers of a biotechnology startup firm agreed to participate in a system dynamics modeling project to help them think about the firm's growth strategy. The article describes how the model was created and used to stimulate debate and discussion about growth management. The paper highlights several novel features about the process used for capturing management team knowledge. A heavy emphasis was placed on mapping the operating structure of the factory and distribution channels. Qualitative modeling methods (structural diagrams, descriptive variable names, and friendly algebra) were used to capture the management team's descriptions of the business. Simulation scenarios were crafted to stimulate debate about strategic issues such as capacity allocation, capacity expansion, customer recruitment, customer retention, and market growth, and to engage the management team in using the computer to design strategic scenarios. The article concludes with comments on the impact of the project.
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Most of water distribution systems (WDS) need rehabilitation due to aging infrastructure leading to decreasing capacity, increasing leakage and consequently low performance of the WDS. However an appropriate strategy including location and time of pipeline rehabilitation in a WDS with respect to a limited budget is the main challenge which has been addressed frequently by researchers and practitioners. On the other hand, selection of appropriate rehabilitation technique and material types is another main issue which has yet to address properly. The latter can affect the environmental impacts of a rehabilitation strategy meeting the challenges of global warming mitigation and consequent climate change. This paper presents a multi-objective optimization model for rehabilitation strategy in WDS addressing the abovementioned criteria mainly focused on greenhouse gas (GHG) emissions either directly from fossil fuel and electricity or indirectly from embodied energy of materials. Thus, the objective functions are to minimise: (1) the total cost of rehabilitation including capital and operational costs; (2) the leakage amount; (3) GHG emissions. The Pareto optimal front containing optimal solutions is determined using Non-dominated Sorting Genetic Algorithm NSGA-II. Decision variables in this optimisation problem are classified into a number of groups as: (1) percentage proportion of each rehabilitation technique each year; (2) material types of new pipeline for rehabilitation each year. Rehabilitation techniques used here includes replacement, rehabilitation and lining, cleaning, pipe duplication. The developed model is demonstrated through its application to a Mahalat WDS located in central part of Iran. The rehabilitation strategy is analysed for a 40 year planning horizon. A number of conventional techniques for selecting pipes for rehabilitation are analysed in this study. The results show that the optimal rehabilitation strategy considering GHG emissions is able to successfully save the total expenses, efficiently decrease the leakage amount from the WDS whilst meeting environmental criteria.
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We characterize optimal policy in a two-sector growth model with xed coeÆcients and with no discounting. The model is a specialization to a single type of machine of a general vintage capital model originally formulated by Robinson, Solow and Srinivasan, and its simplicity is not mirrored in its rich dynamics, and which seem to have been missed in earlier work. Our results are obtained by viewing the model as a specific instance of the general theory of resource allocation as initiated originally by Ramsey and von Neumann and brought to completion by McKenzie. In addition to the more recent literature on chaotic dynamics, we relate our results to the older literature on optimal growth with one state variable: speci cally, to the one-sector setting of Ramsey, Cass and Koopmans, as well as to the two-sector setting of Srinivasan and Uzawa. The analysis is purely geometric, and from a methodological point of view, our work can be seen as an argument, at least in part, for the rehabilitation of geometric methods as an engine of analysis.
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Includes bibliography
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)