Chung-Piaw Teo

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We propose a semidefinite optimization (SDP) model for the class of minimax two-stage stochastic linear optimization problems with risk aversion. The distribution of second-stage random variables belongs to a set of multivariate distributions with known first and second moments. For the minimax stochastic problem with random objective, we provide a tight(More)
We present the first constant-factor approximation algorithm for a fundamental problem: the store-and-forward packet routing problem on arbitrary networks. Furthermore, the queue sizes required at the edges are bounded by an absolute constant. Thus, this algorithm balances a global criterion (routing time) with a local criterion (maximum queue size) and(More)
In recent years, approximation algorithms based on randomized rounding of fractional optimal solutions have been applied to several classes of discrete optimization problems. In this paper, we describe a class of rounding methods that exploits the structure and geometry of the underlying problem to round fractional solution to 0–1 solution. This is achieved(More)
Automated guided vehicles (AGVs) are increasingly becoming the popular mode of container transport in seaport terminals. These unmanned vehicles are used to transfer containers between ships and storage locations on land. The efficiency of a container terminal is directly related to the amount of time each vessel spends in the port. Hence to maintain(More)
We study the classical stable marriage and stable roommates problems using a polyhedral approach. We propose a new LP formulation for the stable roommates problem, which has a feasible solution if and only if the underlying roommates problem has a stable matching. Furthermore, for certain special weight functions on the edges, we construct a 2-approximation(More)
This paper is motivated by a study of the mechanism used to assign primary school students in Singapore to secondary schools. The assignment process requires that primary school students submit a rank ordered list of six schools to the Ministry of Education. Students are then assigned to secondary schools based on their preferences, with priority going to(More)
We address the problem of evaluating the expected optimal objective value of a 0-1 optimization problem under uncertainty in the objective coefficients. The probabilistic model we consider prescribes limited marginal distribution information for the objective coefficients in the form of moments. We show that for a fairly general class of marginal(More)
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In recent years approximation algorithms based on primal-dual methods have been successfully applied to a broad class of discrete optimization problems. In this paper, we propose a generic primal-dual framework to design and analyze approximation algorithms for integer programming problems of the covering type that uses valid inequalities in its design. The(More)
The Location Model with Risk Pooling (LRMP) seeks to locate distribution centers to minimize the sum of fixed location costs, transportation costs, and inventory costs. The risk-pooling effects of consolidating inventory sites are explicitly handled in the location model. In this paper, we present a stochastic version of the LMRP (SLMRP) that optimizes(More)