ON THE SUSTAINABLE GROWTH IN AN ECONOMY WITH PERFECTLY SUBSTITUTABLE EXHAUSTIBLE RESOURCES

Abstract A model of sustainable economic growth in an economy with two types of exhaustible resources is analyzed. The resources are assumed to be perfect substitutes with marginal rate of substitution varying over time. The optimal control framework is used to characterize the optimal paths under the maximin criterion. It is shown that the resource with increasing productivity is not used before the constant productivity resource is depleted. Afterwards the resource with an increasing productivity is asymptotically depleted as well. The results are based on an assumption that transversality conditions hold. A new sufficient condition for the transversality conditions is derived. Finally, an analogue of Hartwick’s rule for this non‐autonomous case is established.     

FORECASTING MINERAL SUPPLY FROM MINERAL RENT DATA

An optimal control model of exhaustible resources is used to clarify the long run relationship between mineral rent and depletion cost at the industry level. A standard first order condition of the time rate of change of rents is reformulated to reveal that rent data may be used to help forecast the rise in extraction costs resulting from resource depletion. This application of the theory of exhaustible resources is illustrated using historical mineral industry rent and extraction cost data. A forecast of U.S. coal extraction costs, following the method proposed in this paper, suggests that future rates of extraction cost increases will be similar to rates experienced in the past.     

Optimal control of a reflection boundary coefficient in an acoustic wave equation

We seek to optimally control a reflection boundary coefficient for an acoustic wave equation. The goal-quantified by an objective functional- is to drive the solution close to a target by adjusting this coefficient, which acts as a control. The problem is solved by finding the optimal control, which minimizes the objective functional. Then the optimal control is used as a an approximation for an inverse “ identification” problem.     

Asymptotic solution of a singularly perturbed optimal control problem related to the reconstruction of a defective curve

The introduction of “cheap” controls for minimizing the simplest energy functional in an optimal control problem related to the reconstruction of a defective curve necessitates solving a singularly perturbed variational problem with fixed time and fixed ends. The construction of a uniform zero asymptotic approximation to the optimal control in the latter problem permits one to conclude that the optimal trajectories in the original optimal control problem combine a uniform motion in the interior of the time interval with rapid transition layers at the boundaries of the control interval.     

A MIXED CONTROL PROBLEM OF THE MANAGEMENT OF NATURAL RESOURCES

In this paper, we study the optimal solutions of a model of natural resource management which allows for both impulse and continuous harvesting policies. This type of model is known in the literature as mixed optimal control problem. In the resource management context, each type of control represents a different harvesting technology, which has a different cost. In particular, we want to know when the following conjecture made by Clark is an optimal solution to this mixed optimal control problem: if the harvesting capacity is unlimited, it is optimal to jump immediately to the steady state of the continuous time problem and then to stay there. We show that under a particular relationship between the continuous and the impulse profit function, the conjecture made by Clark is true. In other cases, however, it is either better to use only continuous control variables or to jump to resource levels which are smaller than the steady state and then let the resource grow back to the steady state. These results emphasize the importance of the cost functions in the modeling of natural resource management.     

Nonconvex and relaxed infinite-horizon optimal control problems

In this paper, we consider the Lagrange problem of optimal control defined on an unbounded time interval in which the traditional convexity hypotheses are not met. Models of this form have been introduced into the economics literature to investigate the exploitation of a renewable resource and to treat various aspects of continuous-time investment. An additional distinguishing feature in the models considered is that we do not assume a priori that the objective functional (described by an improper integral) is finite, and so we are led to consider the weaker notions of overtaking and weakly overtaking optimality. To treat these models, we introduce a relaxed optimal control problem through the introduction of chattering controls. This leads us naturally to consider the relationship between the original problem and the convexified relaxed problem. In particular, we show that the relaxed problem may be viewed as a limiting case for the original problem. We also present several examples demonstrating the applicability of our results.     

On necessary optimality conditions for infinite-horizon economic growth problems with locally unbounded instantaneous utility function

We consider a class of infinite-horizon optimal control problems that arise in studying models of optimal dynamic allocation of economic resources. In a typical problem of that kind the initial state is fixed, no constraints are imposed on the behavior of the admissible trajectories at infinity, and the objective functional is given by a discounted improper integral. Earlier, for such problems, S.M. Aseev and A.V. Kryazhimskiy in 2004–2007 and jointly with the author in 2012 developed a method of finite-horizon approximations and obtained variants of the Pontryagin maximum principle that guarantee normality of the problem and contain an explicit formula for the adjoint variable. In the present paper those results are extended to a more general situation where the instantaneous utility function need not be locally bounded from below. As an important illustrative example, we carry out a rigorous mathematical investigation of the transitional dynamics in the neoclassical model of optimal economic growth.     

可耗竭性资源从价税与累积开采量的关系研究——基于Hotelling模型的改进

提高可耗竭性资源累积开采量对解决我国资源短缺和资源开采效率低下并存的问题具有重要的意义。在增加了开采成本随累积开采量递增的假设下,本文首先对Hotelling模型做了改进。其次,运用最优控制方法,以完全竞争市场为比较基准,本文研究了垄断市场下从价税与累积开采量之间的关系。研究发现:第一,当从价税税率为零时,垄断市场下的累积开采量低于完全竞争市场下的累积开采量。第二,当从价税税率大于零时,征收从价税进一步降低了垄断市场下的累积开采量。第三,当从价税税率小于零时,征收从价税有利于提高垄断市场下的累积开采量。     

Time-cost trade-off via optimal control theory in Markov PERT networks

We develop a new analytical model for the time-cost trade-off problem via optimal control theory in Markov PERT networks. It is assumed that the activity durations are independent random variables with generalized Erlang distributions, in which the mean duration of each activity is a non-increasing function of the amount of resource allocated to it. Then, we construct a multi-objective optimal control problem, in which the first objective is the minimization of the total direct costs of the project, in which the direct cost of each activity is a non-decreasing function of the resources allocated to it, the second objective is the minimization of the mean of project completion time and the third objective is the minimization of the variance of project completion time. Finally, two multi-objective decision techniques, viz, goal attainment and goal programming are applied to solve this multi-objective optimal control problem and obtain the optimal resources allocated to the activities or the control vector of the problem     

An optimization‐based domain decomposition method for numerical simulation of the incompressible Navier‐Stokes flows

This article is concerned about an optimization‐based domain decomposition method for numerical simulation of the incompressible Navier‐Stokes flows. Using the method, an classical domain decomposition problem is transformed into a constrained minimization problem for which the objective functional is chosen to measure the jump in the dependent variables across the common interfaces between subdomains. The Lagrange multiplier rule is used to transform the constrained optimization problem into an unconstrained one and that rule is applied to derive an optimality system from which optimal solutions may be obtained. The optimality system is also derived using “sensitivity” derivatives instead of the Lagrange multiplier rule. We consider a gradient‐type approach to the solution of domain decomposition problem. The results of some numerical experiments are presented to demonstrate the feasibility and applicability of the algorithm developed in this article. © 2009 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2011     

“NET INVESTMENT” AND SUSTAINABILITY

ABSTRACT. We comment on research showing when constant consumption implies zero “net investment.” We also report on the use of ‘net investment “or” genuine savings “as an indicator of sustainability in abstract economies, with exhaustible resources and inherent nonconstant consumption paths. In particular, the use of the current percentage change in” net investment “is reported on.     

Multi-level defense system models: overcoming by means of attacks with several phase constraints

The Germeyer “defense–attack” model is modified to allow for an echeloned defence system in a given direction. The model is a special case of the terminal-type discrete optimal control problem, and it can be solved using the subgradient-descent method. The posed control problem refines the resource level-distribution problem for a given direction, counting more general constraints with allowance for the action abilities of defense tools at various borders.     

Optimising R and D expenditure in the development of resource substitutes1

This paper derives analytical and numerical solutions to a model of the optimal allocation of national economic resources between consumption, investment, and research and development. The research and development activity is a stochastic process which may produce a substitute for an exhaustible but currently essential natural resource. We investigate how the optimal policy varies with the parameters of the economy, and with the specification of the stochastic R and D process.     

不确定条件下可可耗竭资源与可再生资源的博弈分析

能源是经济可持续发展的重要的物质基础.在能源开发时间路径上,不可再生资源面临资源储量的约束,可再生资源面临技术水平的约束.R&D投资可以促进技术进步.但是不论是可耗竭资源的储量还是技术进步水平都具有很大的不确定性.就此情形构建了基于两类能源的生产者利润最大化为目标的随机动态微分博弈,研究不确定性对能源市场均衡的影响.     

Constant Sustainable Consumption Rate in Optimal Growth with Exhaustible Resources

The problem of optimal growth with an exhaustible resource deposit under R. M. Solow's criterion of maximum sustainable consumption rate, previously formulated as a minimum-resource-extraction problem, is shown to be a Mayer-type optimal-control problem. The exact solution of the relevant firstorder necessary conditions for optimality is derived for a Cobb-Douglas production function, whether or not the constant unit resource extraction cost vanishes. The related problem of maximizing the terminal capital stock over an unspecified finite planning period is investigated for the development of more efficient numerical schemes for the solution of multigrade-resource deposit problems. The results for this finite-horizon planning problem are also important from a theoretical viewpoint, since they elucidate the economic content of the optimal growth paths for infinite-horizon problems.     

Dynamic decentralization of harvesting constraints in the management of tychastic evolution of renewable resources

This study proposes a new framework to tackle the uncertainty that prevails in the exploitation of renewable resources. It deals with the question of how to guarantee both a minimum multi-species harvest and the renewal of resources when their evolutions are uncertain. The problem is twofold: to decentralize a global constraint (on a multi-species harvest) into local constraints (on the resources of the different species) and, then, to use a “tychastic” approach necessitating only the forecasts of the lowers bounds of the resource growth rates. This study, formulated as a “tychastic” regulated system with viability constraints, departs from stochastic approaches generally used to deal with uncertain situations. It provides the time dependent harvesting rule allowing to always comply with a minimum harvest objective and resources replenishment thresholds whatever happens and a tychastic measure of risk viability in terms of minimum resources initially required. To solve this problem involving global and local constraints a new method that decentralizes the constraints has been devised. An example is presented whose numerical results are obtained thanks to a dedicated software using mathematical and algorithmic tools of viability theory.     

REVIEW OF DYNAMIC OPTIMIZATION METHODS IN RENEWABLE NATURAL RESOURCE MANAGEMENT

In recent years, the applications of dynamic optimization procedures in natural resource management have proliferated. A systematic review of these applications is given in terms of a number of optimization methodologies and natural resource systems. Optimization methods are characterized by (1) the mathematical model used to describe a natural resource system, (2) a set of feasible strategies available to the resource manager, and (3) an objective functional by which to measure benefits and costs of strategies. A formal statement of the control problem is used to describe six approaches to optimal utilization of renewable natural resources: variational mathematics, specifically Pontryagin's Maximum Principle; dynamic programming; linear programming; nonlinear programming; simulation-optimization; and classical procedures. Solution methodologies are illustrated for each of these approaches, and examples from the ecological and natural resource literature are described for various subject matter areas. Applications are highlighted in terms of model structures, objective functionals, and system constraints. To the extent possible, optimal management patterns are characterized. Finally, the applicability of the methods to renewable natural resource systems are compared in terms of system complexity, system size, and precision of the optimal solutions. Recommendations are made concerning the appropriate methods for certain kinds of biological resource problems.     

Minimizing the ruin probability allowing investments in two assets: a two-dimensional problem

We consider in this paper that the reserve of an insurance company follows the classical model, in which the aggregate claim amount follows a compound Poisson process. Our goal is to minimize the ruin probability of the company assuming that the management can invest dynamically part of the reserve in an asset that has a positive fixed return. However, due to transaction costs, the sale price of the asset at the time when the company needs cash to cover claims is lower than the original price. This is a singular two-dimensional stochastic control problem which cannot be reduced to a one-dimensional problem. The associated Hamilton–Jacobi–Bellman (HJB) equation is a variational inequality involving a first order integro-differential operator and a gradient constraint. We characterize the optimal value function as the unique viscosity solution of the associated HJB equation. For exponential claim distributions, we show that the optimal value function is induced by a two-region stationary strategy (“action” and “inaction” regions) and we find an implicit formula for the free boundary between these two regions. We also study the optimal strategy for small and large initial capital and show some numerical examples.     

Maximization of the total population in a reaction–diffusion model with logistic growth

This paper is concerned with a nonlinear optimization problem that naturally arises in population biology. We consider the effect of spatial heterogeneity on the total population of a biological species at a steady state, using a reaction–diffusion logistic model. Our objective is to maximize the total population when resources are distributed in the habitat to control the intrinsic growth rate, but the total amount of resources is limited. It is shown that under some conditions, any local maximizer must be of “bang–bang” type, which gives a partial answer to the conjecture addressed by Ding et al. (Nonlinear Anal Real World Appl 11(2):688–704, 2010). To this purpose, we compute the first and second variations of the total population. When the growth rate is not of bang–bang type, it is shown in some cases that the first variation becomes nonzero and hence the resource distribution is not a local maximizer. When the first variation becomes zero, we prove that the second variation is positive. These results implies that the bang–bang property is essential for the maximization of total population.     

Strong controllability and optimal control of the heat equation with a thermal source

In this paper we consider an optimal control system described byn-dimensional heat equation with a thermal source. Thus problem is to find an optimal control which puts the system in a finite time T, into a stationary regime and to minimize a general objective function. Here we assume there is no constraints on control. This problem is reduced to a moment problem.We modify the moment problem into one consisting of the minimization of a positive linear functional over a set of Radon measures and we show that there is an optimal measure corresponding to the optimal control. The above optimal measure approximated by a finite combination of atomic measures. This construction gives rise to a finite dimensional linear programming problem, where its solution can be used to determine the optimal combination of atomic measures. Then by using the solution of the above linear programming problem we find a piecewise-constant optimal control function which is an approximate control for the original optimal control problem. Finally we obtain piecewise-constant optimal control for two examples of heat equations with a thermal source in one-dimensional.