[1] The objective of this paper is to present a genetic algorithm-based stochastic dynamic programming (GA-based SDP) to cope with the dimensionality problem of a multiple-reservoir system. The joint long-term operati...
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[1] The objective of this paper is to present a genetic algorithm-based stochastic dynamic programming (GA-based SDP) to cope with the dimensionality problem of a multiple-reservoir system. The joint long-term operation of a parallel reservoir system in the Feitsui and Shihmen reservoirs in northern Taiwan demonstrates the successful application of the proposed GA-based SDP model. Within the case study system it is believed that GA is a useful technique in supporting optimization. Though the employment of GA-based SDP may be time consuming as it proceeds through generation by generation, the model can overcome the "dimensionality curse'' in searching solutions. Simulation results show Feitsui's surplus water can be utilized efficiently to fill Shihmen's deficit water without affecting Feitsui's main purpose as Taipei city's water supply. The optimal joint operation suggests that Feitsui, on average, can provide 650,000 m(3)/day and 920,000 m(3)/day to Shihmen during the wet season and dry season, respectively.
This paper is concerned with an investor trading in multiple securities over many time periods in order to meet an outstanding liability at some future date. The investor is concerned with maximizing the expected prof...
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This paper is concerned with an investor trading in multiple securities over many time periods in order to meet an outstanding liability at some future date. The investor is concerned with maximizing the expected profits from portfolio rebalancing under an initial wealth restriction to meet the future liabilities. We formulate the problem as a discrete-time stochastic optimization model and allow asset prices to have continuous probability distributions on compact domains. For the case of Markovian price uncertainty and convex terminal liability, we develop a simplicial approximation, under which bounds on the problem can be computed efficiently. Computations only require evaluating a dynamicprogramming recursion, which thus, allows its application to problems with a large number of trading periods. The bounds are tight in that they are exact in certain cases. Numerical results are given to demonstrate the computational efficiency of the procedure.
A large number of schemes exist around the world to conserve or establish target natural vegetation communities. These include voluntary agri-environmental contracts, which aim to establish a target vegetation communi...
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A large number of schemes exist around the world to conserve or establish target natural vegetation communities. These include voluntary agri-environmental contracts, which aim to establish a target vegetation community by compensating farmers to reduce stocking rates. These contracts initiate a stochastic vegetation succession which increases the probability of establishing the target vegetation community. To ensure the scheme is achieving its objectives, regulators monitor the vegetation succession and decide whether a contract should stop or continue. If vegetation succession can be represented by a Markov chain, the regulator's problem of when to monitor, the best monitoring method and when to stop or continue a contract can be solved by a partially observed Markov decision process (POMDP). The results, for the conservation and restoration of heather Moorland in the Cambrian Mountains of Wales, show that the frequency and quality of monitoring depends upon monitoring costs and the regulators prior probabilities for the vegetation state. (c) 2005 Elsevier B.V. All fights reserved.
In this paper, we describe the practical application of a flexibility-based management approach to new product development, highlighting advantages, and limitations of this methodology. The model is concerned with the...
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In this paper, we describe the practical application of a flexibility-based management approach to new product development, highlighting advantages, and limitations of this methodology. The model is concerned with the resolution of uncertainty over the product development life cycle and deals with technical, market, and cost factors all together. To this end, we consider a real options model, which uses multidimensional decision trees, to assess the development process of a high-technology product, namely, the Adaptive Optics Scanning Laser Ophthalmoscope. Moreover, we show how this project could be managed by estimating its value and determining optimal managerial actions to be taken at each review stage of the new product development process. Finally, we draw conclusions about this model's general utility and particular challenges associated with its use as a product development tool, and emphasize the need to consider a multidimensional model, instead of a single dimensional one.
作者：
Spring, DAKennedy, JOSMonash Univ
Australian Ctr Biodivers Anal Policy & Management Sch Biol Sci Clayton Vic 3800 Australia La Trobe Univ
Dept Econ & Finance Bundoora Vic 3083 Australia
The problem of determining the optimal age at which to cut trees on four stands, and optimal fire protection expenditure, is posed. The objective is to maximise the resulting expected returns from timber and the expec...
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The problem of determining the optimal age at which to cut trees on four stands, and optimal fire protection expenditure, is posed. The objective is to maximise the resulting expected returns from timber and the expected value of the continued existence of an endangered possum species that relies on old growth for nesting. dynamicprogramming is used to solve the problem. Existence values for the possum are based on the results of a detailed contingent valuation survey. A stochastic metapopulation model is developed for estimating end-stage survival probabilities of the possum dependent on start-of-stage tree ages and occupancies. The sensitivity of optimal cutting and fire-protection policies to possum existence values, the rate of discount and the cost of reducing fire risk is investigated. The study demonstrates the scope of the combined use of simulation and dynamic optimisation for addressing land management problems involving conservation of species threatened with extinction. (c) 2005 Elsevier B.V. All rights reserved.
Climate change is predicted to increase fire frequency and exacerbate water scarcity. The effect of these changes on the tree harvest decision in a forested catchment is investigated using stochasticdynamic programmi...
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Climate change is predicted to increase fire frequency and exacerbate water scarcity. The effect of these changes on the tree harvest decision in a forested catchment is investigated using stochastic dynamic programming, taking a stand of mountain ash (Eucalyptus regnans) in south-eastern Australia as a case study. We find that for a range of water and carbon sequestration values, it is optimal to cease harvesting in the absence of climate change. Whether it is optimal to do so under climate change will depend on the magnitude of the increases in fire frequency and water value. Potential increases in forest productivity also have a significant impact on the tree harvest decision. (c) 2005 Elsevier Ltd. All rights reserved.
This paper presents a Genetic Algorithm (GA) model for finding the optimal operating policy of a multi-purpose reservoir, located on the river Pagladia, a major tributary of the river Brahmaputra. A synthetic monthly ...
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This paper presents a Genetic Algorithm (GA) model for finding the optimal operating policy of a multi-purpose reservoir, located on the river Pagladia, a major tributary of the river Brahmaputra. A synthetic monthly streamflow series of 100 years is used for deriving the operating policy. The policies derived by the GA model are compared with that of the stochastic dynamic programming (SDP) model on the basis of their performance in reservoir simulation for 20 years of historic monthly streamflow. The simulated result shows that GA-derived policies are promising and competitive and can be effectively used for reservoir operation.
The existing literature (i) examines bycatch and discard behavior in a static framework and (ii) treats bycatch as a deterministic process uniform across vessels. Using a dynamic representative agent model in a two-st...
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The existing literature (i) examines bycatch and discard behavior in a static framework and (ii) treats bycatch as a deterministic process uniform across vessels. Using a dynamic representative agent model in a two-stock resource, this paper explores strategic interactions between a social planner and two groups of harvesters, one of which imposes a stochastic '' technological externality '' (bycatch) on the other. In addition to limitations on entry and the number of trips taken in each industry, three bycatch control instruments are compared to the unconstrained case: taxes, trip limits, and value-based quotas. Implementation and enforcement costs aside, taxes dominate both types of quota, and value limits outperform trip limits by eliminating one type of discarding. In simulations, relative performance depends upon variance in the bycatch process, differences in the ex vessel prices of stocks, relative efficiency of the harvester types, and fixed costs on the trip and industry margins. (c) 2004 Elsevier Inc. All rights reserved.
The article discusses various reports about mathematician Arie Hordijk published within the issue, including one by Sheldon Ross on the use of antithetic variables.
The article discusses various reports about mathematician Arie Hordijk published within the issue, including one by Sheldon Ross on the use of antithetic variables.
In this article, we show how the degree of risk aversion, discounting, and preference for intertemporal substitution for a natural resource manager can be structurally estimated within a recursive utility framework. W...
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In this article, we show how the degree of risk aversion, discounting, and preference for intertemporal substitution for a natural resource manager can be structurally estimated within a recursive utility framework. We focus on the management of a reservoir in California, and test the data for consistency with a recursive utility model specification versus standard time-additive separability. The results show that the data are consistent with a risk-averse manager with recursive preferences. The data also reject time-additive separability, with or without risk aversion, such as the standard constant relative risk aversion utility model. The improvement in model fit when recursive preferences are used is notable.
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