Duality and Penalization in Optimization via an Augmented Lagrangian Function with Applications

This paper aims to establish duality and exact penalization results for the primal problem of minimizing an extended real-valued function in a reflexive Banach space in terms of a valley-at-0 augmented Lagrangian function. It is shown that every weak limit point of a sequence of optimal solutions generated by the valley-at-0 augmented Lagrangian problems is a solution of the original problem. A zero duality gap property and an exact penalization representation between the primal problem and the valley-at-0 augmented Lagrangian dual problem are obtained. These results are then applied to an inequality and equality constrained optimization problem in infinite-dimensional spaces and variational problems in Sobolev spaces, respectively. The first author was supported by the Research Committee of Hong Kong Polytechnic University, by Grant 10571174 from the National Natural Science Foundation of China and Grant 08KJB11009 from the Jiangsu Education Committee of China. The second author was supported by Grant BQ771 from the Research Grants Council of Hong Kong. We are grateful to the referees for useful suggestions which have contributed to the final presentation of the paper.     

Lower-Order Penalization Approach to Nonlinear Semidefinite Programming

In this paper, we reformulate a nonlinear semidefinite programming problem into an optimization problem with a matrix equality constraint. We apply a lower-order penalization approach to the reformulated problem. Necessary and sufficient conditions that guarantee the global (local) exactness of the lower-order penalty functions are derived. Convergence results of the optimal values and optimal solutions of the penalty problems to those of the original semidefinite program are established. Since the penalty functions may not be smooth or even locally Lipschitz, we invoke the Ekeland variational principle to derive necessary optimality conditions for the penalty problems. Under certain conditions, we show that any limit point of a sequence of stationary points of the penalty problems is a KKT stationary point of the original semidefinite program. Communicated by Y. Zhang This work was supported by a Postdoctoral Fellowship of Hong Kong Polytechnic University and by the Research Grants Council of Hong Kong.     

A three-dimensional voting system in Hong Kong

The voting system of the Legislative Council of Hong Kong (Legco) is sometimes unicameral and sometimes bicameral, depending on whether the bill is proposed by the Hong Kong government. Therefore, although without any representative within Legco, the Hong Kong government has certain degree of legislative power – as if there is a virtual representative of the Hong Kong government within the Legco. By introducing such a virtual representative of the Hong Kong government, we show that Legco is a three-dimensional voting system. We also calculate two power indices of the Hong Kong government through this virtual representative and consider the C-dimension and the W-dimension of Legco. Finally, some implications of this Legco model to the current constitutional reform in Hong Kong will be given.     

Convergence Results for Weak Efficiency in Vector Optimization Problems with Equilibrium Constraints

In this paper, we consider weak efficiency in vector optimization problems with equilibrium constraints. We obtain results on the convergence of the marginal map, the value, and the solution sets. This research was supported by Hong Kong Polytechnic University under Grant G-YY33 and by National Science Foundation of China under Grant 10401043. The authors express their gratitude to Professor Guangya Chen for careful reading of an earlier version of this paper. The authors are grateful to the anonymous referees for helpful comments and constructive suggestions.     

Merit functions in vector optimization

We study the weak domination property and weakly efficient solutions in vector optimization problems. In particular scalarization of these problems is obtained by virtue of some suitable merit functions. Some natural conditions to ensure the existence of error bounds for merit functions are also given. This research was supported by a direct grant (CUHK) and an Earmarked Grant from the Research Grant Council of Hong Kong.     

A Gradient-based Continuous Method for Large-scale Optimization Problems

In this paper, we study a gradient-based continuous method for large-scale optimization problems. By converting the optimization problem into an ODE, we are able to show that the solution trajectory of this ODE tends to the set of stationary points of the original optimization problem. We test our continuous method on large-scale problems available in the literature. The simulation results are very attractive.This research was supported in part by Grants FRG/99-00/II-23 and FRG/00-0l/II-63 of Hong Kong Baptist University and the Research Grant Council of Hong Kong.     

How Pythagoras' theorem is taught in Czech Republic,Hong Kong and Shanghai: A case study

This paper attempts to explore certain characteristics of the mathematics classroom by investigating how teachers from three different cultures, namely, the Czech Republic, Hong Kong and Shanghai, handle Pythagoras' theorem at eighth grade. Based on a fine-grained analysis of one lesson, from each of the three places, some features in terms of the ways of handling the same topic were revealed, as follows: the Hong Kong teacher and the Shanghai teacher emphasized exploring Pythagoras' theorem, the Shanghai teacher seemed to emphasize mathematical proofs, while the Czech teacher and the Hong Kong teacher tended to verify the theorem visually. It was found that the Czech teacher and the Hong Kong teacher put stress on demonstrating with some degree of student input in the process of learning. On the other hand, the Shanghai teacher demonstrated a constructive learning scenario: students were actively involved in the process of learning under the teacher's control through a series of deliberate activities. Regarding the classroom exercises, the Shanghai teacher tended to vary problems implicitly within a mathematical context, while the teachers in the other two places preferred varying problems explicitly within both mathematical and daily life contexts.     

Convergence Analysis of a Class of Penalty Methods for Vector Optimization Problems with Cone Constraints

In this paper, we consider convergence properties of a class of penalization methods for a general vector optimization problem with cone constraints in infinite dimensional spaces. Under certain assumptions, we show that any efficient point of the cone constrained vector optimization problem can be approached by a sequence of efficient points of the penalty problems. We also show, on the other hand, that any limit point of a sequence of approximate efficient solutions to the penalty problems is a weekly efficient solution of the original cone constrained vector optimization problem. Finally, when the constrained space is of finite dimension, we show that any limit point of a sequence of stationary points of the penalty problems is a KKT stationary point of the original cone constrained vector optimization problem if Mangasarian–Fromovitz constraint qualification holds at the limit point.This work is supported by the Postdoctoral Fellowship of Hong Kong Polytechnic University.     

Necessary and Sufficient Conditions for Weak No-Arbitrage in Securities Markets with Frictions

In this paper we consider a financial market model with frictions which include transaction costs, bid-ask spread and taxes. By using optimization, linear and nonlinear programming and convex programming techniques, several necessary and sufficient conditions are derived for the weak no-arbitrage. Some results on state prices are also provided. The results of this paper can provide at least some theoretical insight to the problem. This research was supported in part by a grant of the National Excellent Ph.D. Thesis Project of China (No. 200267), a grant of the National Natural Science Foundation of China (No. 10171115), a “Tenth Five-Year Plan” project of Ministry of Education of China (No. 01JA630009), a grant of the Natural Science Foundation of Guangdong Province (No. 011193), two grants from the Research Grants Council of Hong Kong (CityU 1081/02E, HKU 7139/01H), and a research grant of the University of Hong Kong.     

Optimal Consumption Portfolio and No-Arbitrage with Nonproportional Transaction Costs

In this paper we consider a finite-state financial market with non-proportional transaction cost and bid-ask spreads. The transaction cost consists of two parts: a fixed cost and a proportional cost to the size of transaction. We show that the existence of an optimal consumption policy implies that the market has no strong arbitrage; the opposite, however, is not true, i.e., no strong arbitrage does not imply the existence of an optimal consumption policy. This is in sharp contrast with the case of proportional transaction cost and other cases reported in the literature, where no strong arbitrage is equivalent to the existence of an optimal consumption policy. We also study the relationship between weak arbitrage and strong arbitrage. Different from the market with proportional transaction cost, we find that these two forms of arbitrage are equivalent unless the fixed cost is zero. A necessary and sufficient condition for the existence of an optimal consumption policy is also obtained. Supported by CAS, NSFC, RGC of Hong Kong and NSF under Grant No. DMI-0196084 and DMI-0200306.     

A Continuous Method for Convex Programming Problems

In this paper, we present a continuous method for convex programming (CP) problems. Our approach converts first the convex problem into a monotone variational inequality (VI) problem. Then, a continuous method, which includes both a merit function and an ordinary differential equation (ODE), is introduced for the resulting variational inequality problem. The convergence of the ODE solution is proved for any starting point. There is no Lipschitz condition required in our proof. We show also that this limit point is an optimal solution for the original convex problem. Promising numerical results are presented.This research was supported in part by Grants FRG/01-02/I-39 and FRG/01-02/II-06 of Hong Kong Baptist University and Grant HKBU2059/02P from the Research Grant Council of Hong Kong.The author thanks Professor Bingsheng He for many helpful suggestions and discussions. The author is also grateful for the comments and suggestions of two anonymous referees. In particular, the author is indebted to one referee who drew his attention to References 15, 17, 18.     

Conception of expert mathematics teacher: a comparative study between Hong Kong and Chongqing

This paper reports the similarities and differences in how “expert mathematics teacher” is conceptualized by mathematics educators in Hong Kong and Chongqing, two cities in China which share similar but different cultural and social backgrounds. Thirty-seven mathematics education researchers, school principals with mathematics education background, and mathematics teachers were interviewed on their perceptions of expert mathematics teacher. It is found that in both cities an expert mathematics teacher should have a profound knowledge base in mathematics, teaching, and students; strong ability in teaching; and a noble personality and a spirit of life-long learning. As for differences, an expert mathematics teacher should have the ability to conduct research, mentor other teachers, and have profound knowledge of examination and educational theories in Chongqing. These attributes were not found in Hong Kong. These similarities and differences are discussed, and relevant social and cultural factors in the two contexts are examined.     

Proximal Point Algorithms for General Variational Inequalities

This paper presents a unified framework of proximal point algorithms (PPAs) for solving general variational inequalities (GVIs). Some existing PPAs for classical variational inequalities, including both the exact and inexact versions, are extended to solving GVIs. Consequently, several new PPA-based algorithms are proposed. M. Li was supported by NSFC Grant 10571083 and SRFDP Grant 200802861031. L.Z. Liao was supported in part by grants from Hong Kong Baptist University and the Research Grant Council of Hong Kong. X.M. Yuan was supported in part by FRG/08-09/II-40 from Hong Kong Baptist University and NSFC Grant 10701055.     

Subgame Consistent Solutions of a Cooperative Stochastic Differential Game with Nontransferable Payoffs

Subgame consistency is a fundamental element in the solution of cooperative stochastic differential games. In particular, it ensures that the extension of the solution policy to a later starting time and any possible state brought about by the prior optimal behavior of the players would remain optimal. Recently, mechanisms for the derivation of subgame consistent solutions in stochastic cooperative differential games with transferable payoffs have been found. In this paper, subgame consistent solutions are derived for a class of cooperative stochastic differential games with nontransferable payoffs. The previously intractable subgame consistent solution for games with nontransferable payoffs is rendered tractable.This research was supported by the Research Grant Council of Hong Kong, Grant HKBU2056/99H and by Hong Kong Baptist University, Grant FRG/02-03/II16.Communicated by G. Leitmann     

Global Error Bound for the Generalized Linear Complementarity Problem over a Polyhedral Cone

In this paper, the global error bound estimation for the generalized linear complementarity problem over a polyhedral cone (GLCP) is considered. To obtain a global error bound for the GLCP, we first develop some equivalent reformulations of the problem under milder conditions and then characterize the solution set of the GLCP. Based on this, an easily computable global error bound for the GLCP is established. The results obtained in this paper can be taken as an extension of the existing global error bound for the classical linear complementarity problems. This work was supported by the Research Grant Council of Hong Kong, a Chair Professor Fund of The Hong Kong Polytechnic University, the Natural Science Foundation of China (Grant No. 10771120) and the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry.     

Multiple outlier detection in growth curve model with unstructured covariance matrix

Under a normal assumption, Liski (1991,Biometrics,47, 659–668) gave some measurements for assessing influential observations in a Growth Curve Model (GCM) with a known covariance. For the GCM with an arbitrary (p.d.) covariance structure, known as unstructured covariance matrix (UCM), the problems of detecting multiple outliers are discussed in this paper. When a multivariate normal error is assumed, the MLEs of the parameters in the Multiple-Individual-Deletion model (MIDM) and the Mean-Shift-Regression model (MSRM) are derived, respectively. In order to detect multiple outliers in the GCM with UCM, the likelihood ratio testing statistic in MSRM is established and its null distribution is derived. For illustration, two numerical examples are discussed, which shows that the criteria presented in this paper are useful in practice.Supported partially by the WAI TAK Investment and Loan Company Ltd. Research Scholarship of Hong Kong for 1992–93.Supported partially by the Hong Kong UPGC Grant.     

Asymptotics for Kernel Estimation of Slicing Average Third-Moment Estimation

To estimate central dimension-reduction space in multivariate nonparametric rcgression, Sliced Inverse Regression （SIR）, Sliced Average Variance Estimation （SAVE） and Slicing Average Third-moment Estimation （SAT） have been developed, Since slicing estimation has very different asymptotic behavior for SIR, and SAVE, the relevant study has been madc case by case, when the kernel estimators of SIH and SAVE share similar asymptotic properties. In this paper, we also investigate kernel estimation of SAT. We. prove the asymptotic normality, and show that, compared with tile existing results, the kernel Slnoothing for SIR, SAVE and SAT has very similar asymptotic behavior,     

On KKT Points of Homogeneous Programs

Homogeneous programming is an important class of optimization problems. The purpose of this note is to give a truly equivalent characterization of KKT points of homogeneous programming problems, correcting a result given by Lasserre and Hiriart-Urruty in Ref. 1.Communicated by P. TsengThis work was partially supported by the National Natural Science Foundation of China, Grants 10201032 and 70221001, and by the Research Grants Council, Hong Kong, Grant CUHK4180/03E.The authors thank two anonymous referees for valuable remarks and insights that have helped improving the paper.     

Triangular Cm interpolation by rational functions

Two general local C^m triangular interpolation schemes by rational functions from C^m data are proposed for any nonnegative integer m. The schemes can have either 2m+1 order algebraic precision if the required data are given on vertices and edges, or m+E[m/2]+1 or m+1 order algebraic precision if the data are given only at vertices. The orders of the interpolation error are estimated. Examples that show the correctness and effectiveness of the scheme are presented. Supported partially by NSFC under Project 1967108 and Croucher Foundation of Hong Kong; Supported also by FRG of Hong Kong Paptist University.