The concept of Support Vector Regression is extended to a more general class of convex cost functions. It is shown how the resulting convex constrained optimization problems can be eeciently solved by a Primal{Dual Interior Point path following method. Both computational feasibility and improvement of estimation is demonstrated in the experiments.

Regular cost functions were introduced as a quantitative generalisation of regular languages, retaining many of their equivalent characterisations and decidability properties. For instance, stabilisation monoids play the same role for cost functions as monoids do for regular languages. The purpose of this article is to further extend this algebraic approach by generalizing two results on regula...

objective(s): global cerebral ischemia-reperfusion (gcir) causes disturbances in brain functions as well as other organs such as kidney. our aim was to evaluate the protective effects of ellagic acid (ea) on certain renal disfunction after gcir. materials and methods: adult male wistar rats (n=32, 250-300 g) were used. gcir was induced by bilateral vertebral and common carotid arteries occlusio...

This paper presents a multi-objective and multi-service location-allocation model with capacity planning to design a healthcare facilities network through considering a referral system. Therefore, a mixed integer nonlinear programming (MINLP) model containing two objective functions is proposed. The first objective function is  relates to minimization of total opening cost, minimization of tota...

Sufficient optimality conditions are obtained for a nonlinear multiple objective fractional programming problem involving η-semidifferentiable type I-preinvex and related functions. Furthermore, a general dual is formulated and duality results are proved under the assumptions of generalized semilocally type I-preinvex and related functions. Our result generalize the results of Preda [V. Preda, ...

This paper describes a mathematical model for all path length parameters (APL: Average Path Length, LPL: Longest Path Length, and SPL: Shortest Path Length) of Binary Decision Diagrams (BDDs). The proposed model is based on an empirical analysis of randomly generated Boolean functions. The formal core of the developed model is a unique equation for the path-related objective functions over the ...

Reduced ordered Binary Decision Diagrams (BDDs) are a data structure for efficient representation and manipulation of Boolean functions. They are frequently used in logic synthesis and formal verification. In recent practical applications, BDDs are optimized with respect to new objective functions. In this paper we investigate the exact optimization of BDDs with respect to path-related objectiv...

This paper gives a combinatorial proof of a “yes” answer to an open question presented in [1], stated as follows: “given a multilinear polynomial E(x): [0; 1] ! <; is it true that Eb(x) = E(x) b x has a strict local minimum over the discrete set f0;1g for almost all b of sufficiently small norm?” The given combinatorial proof is completed directly by providing a sufficient condition for a conje...

3 Non-linear Objective functions 4 3.1 Production problem with set-up costs . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.2 Piecewise linear cost function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3.3 Piecewise linear convex cost function . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.4 Disjunctive constraints . . . . . . . . . . . . . . . . . . . . . ...