A5100341868- Stochastic processes and financial applications
- Risk and Portfolio Optimization
- Economic theories and models
- Insurance, Mortality, Demography, Risk Management
- Financial Markets and Investment Strategies
- Stability and Control of Uncertain Systems
- Capital Investment and Risk Analysis
- Mathematical Biology Tumor Growth
- Financial Risk and Volatility Modeling
- Monetary Policy and Economic Impact
- Aerospace Engineering and Control Systems
- Climate Change Policy and Economics
- Advanced Control Systems Optimization
- Advanced Optimization Algorithms Research
- Adaptive Dynamic Programming Control
- Optimization and Variational Analysis
- Insurance and Financial Risk Management
- Mathematical and Theoretical Epidemiology and Ecology Models
- Stability and Controllability of Differential Equations
- Advanced Mathematical Modeling in Engineering
- Advanced Sensor and Control Systems
- Supply Chain and Inventory Management
- Neural Networks Stability and Synchronization
- Adaptive Control of Nonlinear Systems
- Supply Chain Resilience and Risk Management
Hong Kong Polytechnic University
2016-2025
Sun Yat-sen University
2005-2025
Guangzhou Huali College
2025
Yuli Hospital
2025
Nicholls State University
2009-2025
Hebei University
2024
Xi'an Polytechnic University
2017-2024
Sichuan International Studies University
2009-2022
Tianjin University of Technology
2021
Jiaying University
2020-2021
This paper is concerned with a stochastic linear quadratic (LQ) optimal control problem. The notions of open-loop and closed-loop solvabilities are introduced. A simple example shows that these two different. Closed-loop solvability established by means the corresponding Riccati equation, which implied uniform convexity cost functional. Conditions ensuring functional discussed, including issue how negative weighting matrix-valued function $R(\cdot)$ can be. Finiteness LQ problem...
This paper is concerned with mean-variance portfolio selection problems in continuous-time under the constraint that short-selling of stocks prohibited. The problem formulated as a stochastic optimal linear-quadratic (LQ) control problem. However, this LQ not conventional one (portfolio) constrained to take nonnegative values due no-shorting restriction, and thereby usual Riccati equation approach (involving "completion squares") does apply directly. In addition, corresponding...
Purpose The purpose of this paper is to provide a theoretical model supply chain agility and, based on that, develop research framework for investigating linkages between and firm competitiveness. Design/methodology/approach conceptual introduced here an inter‐disciplinary literature review, which concentrates peer‐reviewed journal papers published within the period 1990‐2007. Among total 583 papers, representative studies are chosen analyzed identify key elements agility, point out issues...
Purpose The purpose of this paper is to develop an instrument measure supply chain agility. Design/methodology/approach development agility scale utilizes examination literature, experience surveys, and expert judges. result a 12‐item with six dimensions. Findings has been rigorously tested validated, which generates high degree confidence in the scale's validity reliability. Originality/value This fulfills identified need for empirically validated reliable enables facilitates future studies...
Purpose This paper aims to investigate the impact of three critical dimensions supply chain resilience, preparedness, alertness and agility, all aimed at increasing a firm’s financial outcomes. In turbulent environment, firms require resilience in their chains prepare for potential changes, detect changes respond actual thus providing superior value. Design/methodology/approach Using survey data from 77 firms, this study develops scales agility. It then tests hypothesized relationships with...
A linear-quadratic (LQ, for short) optimal control problem is consideredfor mean-field stochastic differential equations with constantcoefficients in an infinite horizon. The stabilizability of thecontrol system studied followed by the discussion thewell-posedness LQ problem. can beexpressed as a linear state feedback involving and itsmean, through solutions two algebraic Riccati equations. Thesolvability such kind investigated bymeans semi-definite programming method.
This article adopts a reinforcement learning (RL) method to solve infinite horizon continuous-time stochastic linear quadratic problems, where the drift and diffusion terms in dynamics may depend on both state control. Based Bellman's dynamic programming principle, we presented an online RL algorithm attain optimal control with partial system information. computes control, rather than estimates coefficients, solves related Riccati equation. It only requires local trajectory information,...
This paper is concerned with the discrete-time indefinite mean-field linear-quadratic optimal control problem. The so-called type stochastic problems refer to problem of incorporating means state variables into equations and cost functionals, such as mean-variance portfolio selection problems. A dynamic optimization called be nonseparable in sense programming if it not decomposable by a stage-wise backward recursion. classical dynamic-programming-based methods would fail situations principle...
When a dynamic optimization problem is not decomposable by stage-wise backward recursion, it nonseparable in the sense of programming. The classical programming-based optimal stochastic control methods would fail such situations as principle optimality no longer applies. Among these notorious problems, mean-variance portfolio selection formulation had posed great challenge to our research community until recently. Different from existing literature that invokes embedding schemes and...
In this paper, the finite-horizon and infinite-horizon indefinite mean-field stochastic linear-quadratic optimal control problems are studied. Firstly, open-loop closed-loop strategy for problem introduced, their characterizations, difference relationship thoroughly investigated. The can be defined a fixed initial state, whose existence is characterized via solvability of linear forward-backward equation with stationary conditions convexity condition. On other hand, shown to equivalent any...
The discrete‐time mean‐variance portfolio selection formulation, which is a representative of general dynamic mean‐risk problems, typically does not satisfy time consistency in efficiency (TCIE), i.e., truncated precommitted efficient policy may become inefficient for the corresponding problem. In this paper, we analytically investigate effect constraints on TCIE convex cone‐constrained markets. More specifically, derive semi‐analytical expressions and minimum‐variance signed supermartingale...
An optimal control problem is studied for a linear mean-field stochastic differential equation with quadratic cost functional. The coefficients and the weighting matrices in functional are all assumed to be deterministic. Closed-loop strategies introduced, which require independent of initial states; such nature makes it very useful convenient applications. In this paper, existence an closed-loop strategy system (also called solvability problem) characterized by regular solution coupled two...