When the estimation of the single equation multiple linear regression model is looked upon as an optimization problem, we show how the principles and methods of optimization can assist the analyst in finding an attractive prediction model. We illustrate this with the estimation of a linear prediction model for valuating residential property using regression quantiles. We make use of the linear ...

This paper presents Type-Oriented Logic Meta Programming. The idea is based on a representation of programs as sets of logic propositions focusing on the type properties of the base-language program. This representation allows generation of base-level code from compiletime logic meta programs that manipulate code fragments and their type properties. We apply this idea to Java and present TyRuBa...

Robust explicit/multi-parametric controllers are designed for constrained, linear discrete–time systems with box-constrained states and inputs, involving uncertainty in the left–hand side (LHS) of the Model Predictive Control (MPC) optimization model. Based on previous results, this work presents a new algorithm that features: (i) a dynamic programming reformulation of the MPC optimization, (ii...

In this paper, stochastic programming problems are viewed as parametric programs with respect to the probability distributions of the random coefficients. General results on quantitative stability in parametric optimization are used to study distribution sensitivity of stochastic programs. For recourse and chance constrained models quantitative continuity results for optimal values and optimal ...

This work presents a methodology to derive explicit control laws for hybrid linear systems. The proposed method employs multi-parametric and dynamic programming techniques to dissemble the original MPC formulation into a set of smaller problems, which can be efficiently solved using suitable multi-parametric mixed integer programming algorithms. The solution comprises the envelope of explicit p...

Sun is currently evaluating a number of proposals for adding parametric types to the Java programming language. This paper presents some experiences with types and type safety in the context of C, C++, and Java, and provides some opinions on GenericJava, the leading proposal for parametric types in Java.

We review the recent progress in the design of e cient algorithms for various problems in geometric optimization. The emphasis in this survey is on the techniques used to attack these problems, such as parametric searching, geometric alternatives to parametric searching, prune-and-search techniques for linear programming and related problems, and LP-type problems and their e cient solution.

We consider linear systems of equations A(p)x = b(p),where the parameters p are linearly dependent and come from prescribed boxes, and the sets of solutions (defined in various ways) which have linear boundary. One fundamental problem is to compute a box being inside a parametric solution set. We first consider parametric tolerable solution sets (being convex polyhedrons). For such solution set...

Parametric programming has received a lot of attention in the control literature in the past few years because model predictive controllers (MPC) can be posed in a parametric framework and hence pre-solved offline, resulting in a significant decrease in on-line computation effort. In this paper we survey recent work on parametric linear programming (pLP) from the point of view of the control en...