Optimal control strategies for dividend payments and capital injections in compound Markov binomial risk model with penalties for deficits

2016 ◽  
Vol 46 (10) ◽  
pp. 5072-5092 ◽  
Author(s):  
Jiyang Tan ◽  
Yuhui Ma ◽  
Hanjun Zhang ◽  
Ziqiang Li ◽  
Xiangqun Yang
Keyword(s):  
Optimal Control ◽  
Risk Model ◽  
Control Strategies ◽  
Dividend Payments ◽  
Capital Injections

An Optimal Control Problem in a Risk Model with Stochastic Premiums and Periodic Dividend Payments

2017 ◽  
Vol 34 (03) ◽  
pp. 1740013 ◽  
Author(s):  
Xixi Yang ◽  
Jiyang Tan ◽  
Hanjun Zhang ◽  
Ziqiang Li
Keyword(s):  
Optimal Control ◽  
Markov Chain ◽  
Value Function ◽  
Risk Model ◽  
Control Strategies ◽  
Random Variable ◽  
Time Interval ◽  
Positive Real ◽  
Dividend Payments ◽  
The Value Function

In this paper, a discrete-time risk model is considered. We assume that the premium received in each time interval is a positive real-valued random variable, and the sequence of premiums is a Markov chain. In any time interval the probability of a claim occurrence is related to the premium received in the corresponding period. We discuss control strategies for dividends paid periodically to the shareholders under two cases: absence and presence of ceiling restriction for dividend rates. We provide algorithms and some properties for the optimal control strategies by transforming the value function.

scholarly journals Optimal Dividend and Capital Injection Strategies for a Risk Model under Force of Interest

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Ying Fang ◽  
Zhongfeng Qu
Keyword(s):  
Risk Model ◽  
Risk Process ◽  
Insurance Company ◽  
Threshold Strategy ◽  
Dividend Payments ◽  
Optimal Dividend ◽  
Optimal Injection ◽  
Force Of Interest ◽  
Capital Injections ◽  
Injection Strategies

As a generalization of the classical Cramér-Lundberg risk model, we consider a risk model including a constant force of interest in the present paper. Most optimal dividend strategies which only consider the processes modeling the surplus of a risk business are absorbed at 0. However, in many cases, negative surplus does not necessarily mean that the business has to stop. Therefore, we assume that negative surplus is not allowed and the beneficiary of the dividends is required to inject capital into the insurance company to ensure that its risk process stays nonnegative. For this risk model, we show that the optimal dividend strategy which maximizes the discounted dividend payments minus the penalized discounted capital injections is a threshold strategy for the case of the dividend payout rate which is bounded by some positive constant and the optimal injection strategy is to inject capitals immediately to make the company's assets back to zero when the surplus of the company becomes negative.

Optimal Control of a General Environmental Space

1986 ◽  
Vol 108 (4) ◽  
pp. 330-339 ◽  
Author(s):  
M. A. Townsend ◽  
D. B. Cherchas ◽  
A. Abdelmessih
Keyword(s):  
Optimal Control ◽  
Maximum Principle ◽  
Moisture Content ◽  
Control Strategies ◽  
Switching Control ◽  
The Maximum Principle ◽  
Environmental Space ◽  
And Performance

This study considers the optimal control of dry bulb temperature and moisture content in a single zone, to be accomplished in such a way as to be implementable in any zone of a multi-zone system. Optimality is determined in terms of appropriate cost and performance functions and subject to practical limits using the maximum principle. Several candidate optimal control strategies are investigated. It is shown that a bang-bang switching control which is theoretically periodic is a least cost practical control. In addition, specific attributes of this class of problem are explored.

Optimal Control Strategy for Ice-Storage System Based on Hourly Dynamic Load Simulation

2013 ◽  
Vol 671-674 ◽  
pp. 2515-2519
Author(s):  
Xue Mei Wang ◽  
Zhen Hai Wang ◽  
Xing Long Wu
Keyword(s):  
Optimal Control ◽  
Air Conditioning ◽  
Control Strategies ◽  
Storage System ◽  
Simulation Software ◽  
Ice Storage ◽  
Optimal Control Strategy ◽  
Air Conditioning System ◽  
Energy Plus ◽  
Load Simulation

This project aims to study the optimal control model of the ice-storage system which is theoretically close to the optimal control and also applicable to actual engineering. Using Energy Plus, the energy consumption simulation software, and the simple solution method of optimal control, researchers can analyze and compare the annual operation costs of the ice-storage air-conditioning system of a project in Beijing under different control strategies. Researchers obtained the power rates of the air-conditioning system in the office building under the conditions of chiller-priority and optimal contro1 throughout the cooling season. Through analysis and comparison, they find that after the implementation of optimal control, the annually saved power bills mainly result from non-design conditions, especially in the transitional seasons.

Optimal Control Strategies of Fuel cell/Battery Based Zero-Emission Ships: A Survey

2021 ◽  
Author(s):  
Mohsen Banaei ◽  
Jalil Boudjadar ◽  
Razgar Ebrahimy ◽  
Henrik Madsen
Keyword(s):  
Optimal Control ◽  
Fuel Cell ◽  
Control Strategies ◽  
Zero Emission

Optimal control strategies for the surface hardening of steel

2004 ◽  
Vol 120 ◽  
pp. 325-335
Author(s):  
D. Hömberg ◽  
S. Volkwein ◽  
W. Weiss
Keyword(s):  
Optimal Control ◽  
Surface Hardening ◽  
Control Strategies ◽  
Hot Spot ◽  
Orthogonal Decomposition ◽  
Phase Volume ◽  
The Finite Element Method ◽  
Optimal Temperature ◽  
Real Process ◽  
Proper Orthogonal

We discuss control strategies for the surface hardening of steel with laser or electron beam. The goal is to acchieve a prescribed hardening depth avoiding surface melting. Our mathematical model consists of a system of ODEs for the phase volume fractions coupled with the heat equation. The system is solved semi-implicitely using the finite element method. For the optimal control we discuss two approaches: model reduction using POD (Proper Orthogonal Decomposition) and a feedback control of temperature. The numerical results prove that it is not sufficient to control the surface temperature in order to obtain a uniform hardening depth. Instead the best strategy should be to compute the optimal temperature in the hot spot of the beam by solving the control problem and use this temperature as the set-point for the pyrometer control of the real process.

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