Discrete-time mean variance optimal control of linear systems with Markovian jumps and multiplicative noise

In this article, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noise under three kinds of performance criterions related to the final value of the expectation and variance of the output. In the first problem it is desired to minimise the final variance of the output subject to a restriction on its final expectation, in the second one it is desired to maximise the final expectation of the output subject to a restriction on its final variance, and in the third one it is considered a performance criterion composed by a linear combination of the final variance and expectation of the output of the system. We present explicit sufficient conditions for the existence of an optimal control strategy for these problems, generalising previous results in the literature. We conclude this article presenting a numerical example of an asset liabilities management model for pension funds with regime switching.

Optimal irrigation depth for bean crops considering water constraints and farmer`s risk aversion level

Nowadays, the rising competition for the use of water and environmental resources with consequent restrictions for farmers should change the paradigm in terms of irrigation concepts, or rather, in order to attain economical efficiency other than to supply water requirement for the crop. Therefore, taking into account the social and economical role of bean activity in Brazil, as well as the risk inherent to crop due to its high sensibility to both deficit and excessive water, the optimization methods regarding to irrigation management have become more interesting and essential. This study intends to present a way to determine the optimal water supply, considering different combinations between desired bean yield and level of risk, bringing as a result a graph with the former associated with the latter, depending on different water depths.

Generalized optimal lattice covering of finite-dimensional Euclidean space

A generalization of the classical problem of optimal lattice covering of R-n is considered. Solutions to this generalized problem are found in two specific classes of lattices. The global optimal solution of the generalization is found for R-2. (C) 1998 Elsevier Science Inc. All rights reserved.

The nurse lecturer role in clinical practice conceptualized: helping clinical teachers provide optimal student learning

Despite the fairly wide reporting in the literature of the ma ny roles of clinical supervision by the nursing teacher, little attention has been given to conceptualizing the relative priorities these roles take during the process of supervising nursing students in clinical practice. The purpose of this paper is to consider the manifestations and implications of conflicting roles when nurse lecturers undertake clinical supervision. Previously published research will provide working examples of issues in a conceptual framework for clinical teaching.

The influence of supra-optimal root-zone temperatures on growth and stomatal conductance in Capsicum annuum L.

Pepper (Capsicum annuum L.) plants were grown aeroponically in a Singapore greenhouse under natural diurnally fluctuating ambient shoot temperatures, but at two different root-zone temperatures (RZTs): a constant 20 +/- 2 degrees C RZT and a diurnally fluctuating ambient (A) (25-40 degrees C) RZT, Plants grown at 20-RZT had more leaves, greater leaf area and dry weight than A-RZT plants. Reciprocal transfer experiments were conducted between RZTs to investigate the effect on plant growth, stomatal conductance (g(s)) and water relations. Transfer of plants from A-RZT to 20-RZT increased plant dry weight, leaf area, number of leaves, shoot water potential (Psi(shoot)), and g(s); while transfer of plants from 20-RZT to A-RZT decreased these parameters. Root hydraulic conductivity was measured in the latter transfer and decreased by 80% after 23 d at A-RZT. Transfer of plants from 20-RZT to A-RZT had no effect on xylem ABA concentration or xylem nitrate concentration, but reduced xylem sap pH by 0.2 units. At both RZTs, g(s) measured in the youngest fully expanded leaves increased with plant development. In plants with the same number of leaves, A-RZT plants had a higher g(s) than 20-RZT plants, but only under high atmospheric vapour pressure deficit. The roles of chemical signals and hydraulic factors in controlling g(s) of aeroponically grown Capsicum plants at different RZTs are discussed.

Optimal release strategies for biological control agents: an application of stochastic dynamic programming to population management

1. Establishing biological control agents in the field is a major step in any classical biocontrol programme, yet there are few general guidelines to help the practitioner decide what factors might enhance the establishment of such agents. 2. A stochastic dynamic programming (SDP) approach, linked to a metapopulation model, was used to find optimal release strategies (number and size of releases), given constraints on time and the number of biocontrol agents available. By modelling within a decision-making framework we derived rules of thumb that will enable biocontrol workers to choose between management options, depending on the current state of the system. 3. When there are few well-established sites, making a few large releases is the optimal strategy. For other states of the system, the optimal strategy ranges from a few large releases, through a mixed strategy (a variety of release sizes), to many small releases, as the probability of establishment of smaller inocula increases. 4. Given that the probability of establishment is rarely a known entity, we also strongly recommend a mixed strategy in the early stages of a release programme, to accelerate learning and improve the chances of finding the optimal approach.

Using stochastic dynamic programming to determine optimal fire management for Banksia ornata

1. A model of the population dynamics of Banksia ornata was developed, using stochastic dynamic programming (a state-dependent decision-making tool), to determine optimal fire management strategies that incorporate trade-offs between biodiversity conservation and fuel reduction. 2. The modelled population of B. ornata was described by its age and density, and was exposed to the risk of unplanned fires and stochastic variation in germination success. 3. For a given population in each year, three management strategies were considered: (i) lighting a prescribed fire; (ii) controlling the incidence of unplanned fire; (iii) doing nothing. 4. The optimal management strategy depended on the state of the B. ornata population, with the time since the last fire (age of the population) being the most important variable. Lighting a prescribed fire at an age of less than 30 years was only optimal when the density of seedlings after a fire was low (< 100 plants ha(-1)) or when there were benefits of maintaining a low fuel load by using more frequent fire. 5. Because the cost of management was assumed to be negligible (relative to the value of the persistence of the population), the do-nothing option was never the optimal strategy, although lighting prescribed fires had only marginal benefits when the mean interval between unplanned fires was less than 20-30 years.

Modelling socially optimal land allocations for sugar cane growing in North Queensland: a linked mathematical programming and choice modelling study

A modelling framework is developed to determine the joint economic and environmental net benefits of alternative land allocation strategies. Estimates of community preferences for preservation of natural land, derived from a choice modelling study, are used as input to a model of agricultural production in an optimisation framework. The trade-offs between agricultural production and environmental protection are analysed using the sugar industry of the Herbert River district of north Queensland as an example. Spatially-differentiated resource attributes and the opportunity costs of natural land determine the optimal tradeoffs between production and conservation for a range of sugar prices.

Genetic algorithms for design of liquid retaining structure

In this paper, genetic algorithm (GA) is applied to the optimum design of reinforced concrete liquid retaining structures, which comprise three discrete design variables, including slab thickness, reinforcement diameter and reinforcement spacing. GA, being a search technique based on the mechanics of natural genetics, couples a Darwinian survival-of-the-fittest principle with a random yet structured information exchange amongst a population of artificial chromosomes. As a first step, a penalty-based strategy is entailed to transform the constrained design problem into an unconstrained problem, which is appropriate for GA application. A numerical example is then used to demonstrate strength and capability of the GA in this domain problem. It is shown that, only after the exploration of a minute portion of the search space, near-optimal solutions are obtained at an extremely converging speed. The method can be extended to application of even more complex optimization problems in other domains.

A study of high-speed milling characteristics of nitinol

High-speed milling (HSM) has many advantages over conventional machining. Among these advantages, the lower cutting force associated with the machining process is of particular significance for Nitinol alloys because their machined surfaces show less strain hardening. In this article, a systematic study has been carried out to investigate the machining characteristics of a Ni50.6Ti49.4 alloy in HSM. The effects of cutting speed, feed rate, and depth of cut on machined surface characteristics and tool wear are studied. It is found that an increase in cutting speed has resulted in a better surface finish and less work hardening. This is attributed to the reduction of chip cross-sectional area or chip thickness, which thus leads to a lower cutting force or load.

Debt Maturity: Is Long-Term Debt Optimal?

We model and calibrate the arguments in favor and against short-term and long-term debt. These arguments broadly include: maturity premium, sustainability, and service smoothing. We use a dynamic-equilibrium model with tax distortions and government outlays uncertainty, and model maturity as the fraction of debt that needs to be rolled over every period. In the model, the benefits of defaulting are tempered by higher future interest rates. We then calibrate our artificial economy and solve for the optimal debt maturity for Brazil as an example of a developing country and the US as an example of a mature economy. We obtain that the calibrated costs from defaulting on long-term debt more than offset costs associated with short-term debt. Therefore, short-term debt implies higher welfare levels.