• New formulation of topology optimization with uncertain boundary displacement. Existence solutions to continuum formulation. Numerical comparison standard NLP-solver, SDP-solver and non-smooth solver. We present a worst-case approach (TO) for maximum stiffness under displacement parametrized by matrix-valued scaling function times an vector giving its direction. The objective in the TO proble...

This paper presents an efficient observation concerning the enhancement of smart grid (SG) based on optimal placement phasor measurement units (OPP) using nonlinear programming (NLP). The proposed algorithm tries to achieve two objectives: (i) ascertain minimum number (PMUs) and (ii) increase redundancy SG at all buses. Synchronized current voltage phasors are obtained enhance accuracy state es...

Circuit partitioning is a very extensively studied problem. Traditional heuristic methods used to solve these problems degrade in performance when the problem size becomes large. Clustering has been proposed as a method to reduce the problem size, allowing the problem to be solved faster and with more accuracy. In [7] we propose a novel bipartitioning method based on a mathematical formulation ...

This paper addresses the similarity assessment and the retrieval problems in Case-Based Reasoning for case bases consisting of traditional and generalized cases. Previous work focussed on similarity assessment for generalized cases with continuous domains. The similarity assessment problem was formulated as Nonlinear Programm (NLP), which is well known in mathematical optimization. In several r...

Domain adaptation is a challenge for supervised NLP systems because of expensive and time-consuming manual annotated resources. We present a novel method to adapt a supervised coreference resolution system trained on newswire to short narrative stories without retraining the system. The idea is to perform inference via an Integer Linear Programming (ILP) formulation with the features of narrati...

Defender-Attacker Stackelberg games are the foundations of tools deployed for computing optimal patrolling strategies in adversarial domains such as the United states Federal Air Marshals Service and the United States Coast Guard, among others. In Stackelberg game models of these systems the attacker knows only the probability that each target is covered by the defender, but is oblivious to the...

Word embedding models learn vectorial word representations that can be used in a variety of NLP applications. When training data is scarce, these models risk losing their generalization abilities due to the complexity of the models and the overfitting to finite data. We propose a regularized embedding formulation, called Robust Gram (RG), which penalizes overfitting by suppressing the disparity...

In this paper, we propose a walk-based graph kernel that generalizes the notion of treekernels to continuous spaces. Our proposed approach subsumes a general framework for word-similarity, and in particular, provides a flexible way to incorporate distributed representations. Using vector representations, such an approach captures both distributional semantic similarities among words as well as ...

In this work, we present a new Big-M reformulation for Generalized Disjunctive Programs. The proposed MINLP reformulation is stronger than the traditional Big-M, and it does not require additional variables or constraints. We present the new Big-M, and analyze the strength in its continuous relaxation compared to that of the traditional Big-M. The new formulation is tested by solving several in...