State-Constrained Optimal Control of a Coupled Quasilinear Parabolic System Modeling Economic Growth in the Presence of Technological Progress

IF 1.6 2区 数学 Q2 MATHEMATICS, APPLIED
Mohamed Mehdaoui, Deborah Lacitignola, Mouhcine Tilioua
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引用次数: 0

Abstract

We develop an optimal control framework that enables to determine the most-beneficial ways of investing in technology and directing capital within an economy. Our developed framework features three main novelties: the optimization of a cross–diffusion term that incorporates the allocation of capital towards specific regions with higher level of technology; the coupling of technological progress with the capital in the state system; and the inclusion of an inequality constraint imposing that the squared norm of technological progress does not surpass a capacity \(M_A>0\), which is more practical in economic applications. This leads to a new state-constrained optimal control problem which we analyze as follows. First, by examining the weak well-posedness of the dynamics, we identify a threshold parameter \(M^*>0\) such that when \(M_A\ge M^*\), the state-constraint can be omitted. In this case, we deal with a reduced state-unconstrained optimal control problem. On the other hand, when \(M_A<M^*\), the state-constraint is not implicitly incorporated. Consequently, we proceed by a penalization approach to formulate a sequence of state-unconstrained optimal control problems and provide necessary optimality conditions for its associated sequence of locally optimal solutions. Subsequently, we prove that the sequence of locally optimal solutions converges strongly to a locally optimal solution for the original state-constrained optimal control problem and retrieve its necessary optimality conditions. Finally, we perform various numerical simulations to illustrate the effects of optimal investment in technology and optimal capital direction on the economy. This study could offer interesting insights in the perspective of circular economy transition.

技术进步下经济增长耦合拟线性抛物型系统的状态约束最优控制
我们开发了一个最优控制框架,能够确定最有利的技术投资方式,并在经济中引导资本。我们开发的框架具有三个主要的新颖之处:优化交叉扩散项,将资本配置纳入具有较高技术水平的特定地区;技术进步与国有资本的耦合并且包含一个不等式约束,强制技术进步的平方规范不超过能力\(M_A>0\),这在经济应用中更实际。这导致了一个新的状态约束最优控制问题,我们分析如下。首先,通过检查动力学的弱适定性,我们确定了一个阈值参数\(M^*>0\),这样当\(M_A\ge M^*\)时,状态约束可以省略。在这种情况下,我们处理一个简化的状态无约束最优控制问题。另一方面,当\(M_A<M^*\)时,状态约束没有隐式合并。因此,我们采用惩罚方法构造了一个无状态约束的最优控制问题序列,并为其相关的局部最优解序列提供了必要的最优性条件。随后,我们证明了原状态约束最优控制问题的局部最优解序列强收敛于一个局部最优解,并检索了其必要的最优性条件。最后,我们通过各种数值模拟来说明最优技术投资和最优资本方向对经济的影响。本研究可以从循环经济转型的角度提供有趣的见解。
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来源期刊
CiteScore
3.30
自引率
5.60%
发文量
103
审稿时长
>12 weeks
期刊介绍: The Applied Mathematics and Optimization Journal covers a broad range of mathematical methods in particular those that bridge with optimization and have some connection with applications. Core topics include calculus of variations, partial differential equations, stochastic control, optimization of deterministic or stochastic systems in discrete or continuous time, homogenization, control theory, mean field games, dynamic games and optimal transport. Algorithmic, data analytic, machine learning and numerical methods which support the modeling and analysis of optimization problems are encouraged. Of great interest are papers which show some novel idea in either the theory or model which include some connection with potential applications in science and engineering.
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