The search strategy of a CP solver is determined by the variable and value ordering heuristics it employs and by the branching scheme it follows. Although the effects of variable and value ordering heuristics on search effort have been widely studied, the effects of different branching schemes have received less attention. In this paper we study this effect through an experimental evaluation th...

PURPOSE: Segmented structures such as targets or organs at risk are typically stored as 2D contours contained on evenly spaced cross sectional images (slices). Contour interpolation algorithms are implemented in radiation oncology treatment planning software to turn 2D contours into a 3D surface, however the results differ between algorithms, causing discrepancies in analysis. Our goal was to c...

This paper presents hHDP, a hierarchical algorithm for representing a document collection as a hierarchy of latent topics, based on Dirichlet process priors. The hierarchical nature of the algorithm refers to the Bayesian hierarchy that it comprises, as well as to the hierarchy of the latent topics. hHDP relies on nonparametric Bayesian priors and it is able to infer a hierarchy of topics, with...

While much of the work in the design of convolutional networks over the last five years has revolved around the empirical investigation of the importance of depth, filter sizes, and number of feature channels, recent studies have shown that branching, i.e., splitting the computation along parallel but distinct threads and then aggregating their outputs, represents a new promising dimension for ...

We present an online learning approach to variable branching in branch-and-bound for mixed-integer linear problems. Our approach consists in learning strong branching scores in an online fashion and in using them to take branching decisions. More specifically, numerical scores are used to rank the branching candidates. If, for a given variable, the learned approximation is deemed reliable, then...

The search strategy of a CP solver is determined by the variable and value ordering heuristics it employs and by the branching scheme it follows. Although the effects of variable and value ordering heuristics on search effort have been widely studied, the effects of different branching schemes have received less attention. In this paper we study this effect through an experimental evaluation th...

This paper introduces the optimization algorithm to improve search rate in urban path routing problems using viral infection and local search in urban environment. This algorithm operates based on two different approaches including wavelet transform and genetic algorithm. The variables proposed by driver such as degree of difficulty and difficulty traffic are of the essence in this technique. W...

Abstract Local search algorithms are frequently used to handle complex optimization problems involving binary decision variables. One way of implementing a local procedure is by using mixed-integer programming solver explore neighborhood defined through constraint that limits the number variables whose values allowed change in given iteration. Recognizing not all equally promising when searchin...

Suppose we try to find the global minimum value of the energy function E(r), in which r ∈ R and R is the conformational space of the rotamers. The BnB algorithm executes two steps recursively. The first step is called branching, in which we split the conformational space R into two or more smaller spaces, i.e., R1, R2, . . . , Rm, where R1 ∪ R2 ∪ · · · ∪ Rm = R. If we are able to find r̂i = argm...