Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/85175
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dc.contributorDepartment of Logistics and Maritime Studies-
dc.creatorYuan, Jiguang-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/3643-
dc.language.isoEnglish-
dc.titleComputational optimization of mutual insurance systems: a Quasi-Variational Inequality approach-
dc.typeThesis-
dcterms.abstractIt is well known that the optimal control of a stochastic system represents a general problem which can be found in many areas such as inventory control, financial engineering, and lately federal (national) reserve management, and so on. If the underlying system involves with some fixed transaction costs the problem will turn out to be known as an impulse control problem. The framework of solving this type of problem is initially developed by Bensoussan [10] and Aubin [5]. They proved that the optimal solution to an impulse control problem can be sufficiently characterized by Quasi-Variational Inequality (QVI). With these profound findings and fundamental developments in impulse control theory, a mathematically rigid HJB-QVI system (deterministic), which is formulated in the form of a functional boundary-value problem of non-linear Hamilton-Jacob-Bellman (HJB) equations, has been established as a general methodology for solving impulse control problems (stochastic). In theory, optimal solution to a stochastic impulse control problem can be determined by solving a corresponding deterministic HJB-QVI system. However, in reality, HJB-QVI system of a practical impulse control problem is often too complicated to have an analytical solution in closed forms. As far as we can ascertain from the literature, apart from very few extremely simplified problems [34, 11, 28], closed-form analytical solution to an HJB-QVI system is seldom attainable. In this study, we obtain computational properties of the aforementioned QVI systems associated with impulse control problems, and provide computational methods for solving the QVI systems, which we categorize into two major classes: 1) QVI systems with analytically solvable HJB equations; 2) QVI systems with analytically unsolvable HJB equations. We begin with the study on the class-1 QVI systems. Although general solutions to underlying HJB equation of a class-1 QVI systems are obtainable, the associated QVI system may still need to be solved in non-closed forms. We present the solution for two class-1 type QVI systems in Chapter 2 and Chapter 3. For class-2 QVI systems, to obtain numerical solutions a computational optimization algorithm presented in Chapter 4. In the last chapter we again consider a class-1 QVI system. It has a non-symmetric cost structure, which has particular application in mutual insurance reserve control problem. A novel computation algorithm is developed to determine numerically an optimal (a, A; B, b) policy.-
dcterms.accessRightsopen access-
dcterms.educationLevelPh.D.-
dcterms.extentix, 128 leaves : ill. ; 30 cm.-
dcterms.issued2009-
dcterms.LCSHHong Kong Polytechnic University -- Dissertations.-
dcterms.LCSHInsurance.-
dcterms.LCSHVariational inequalities (Mathematics)-
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