There are two dominant approaches to Chinese word segmentation: word-based and character-based models, each with respective strengths. Prior work has shown that gains in segmentation performance can be achieved from combining these two types of models; however, past efforts have not provided a practical technique to allow mainstream adoption. We propose a method that effectively combines the st...

This paper presents different variants of weight-coding in a genetic algorithm (GA) for solving the multiconstraint knapsack problem (MKP). In this coding, a chromosome is a vector of weights associated with the items of the MKP. The phenotype is obtained by using the weights to generate a modified version of the original problem and applying a decoding heuristic to it. Four techniques of biasi...

Two heuristics for the Linear Ordering Problem are investigated in this paper. heuristics are embedded within a Lagrangian Relaxation framework and are initiated with a construction phase. In this process, some Lagrangian (dual) information is used as an input to guide the construction of initial Linear Orderings. Solutions thus obtained are then submitted to local improvement in an overall pro...

Analytical VLSI placement techniques achieved high solution quality and strong extensibility based on smooth approximation of placement objective and constraints. However, significant room still exist for VLSI placement to improve. We observe at least two sources of placement complexity and inaccuracy, namely, poor predictability for placement metrics and poor controllability of placement const...

We study non-convex quadratic minimization problems under (possibly non-convex) quadratic and linear constraints, and characterize both Lagrangian and Semi-Lagrangian dual bounds in terms of conic optimization. While the Lagrangian dual is equivalent to the SDP relaxation (which has been known for quite a while, although the presented form, incorporating explicitly linear constraints, seems to ...

The analytic center of a polytope P fx Ax b ex g is characterized by a saddle point condition min y R max x S g x y max x S min y R g x y on the Lagrangian function

A central problem of branch and bound methods for global optimization is that lower bounds are often not exact even if the diameter of the subdivided regions shrinks to zero This can lead to a large number of subdivisions preventing the method from terminating in reasonable time For the all quadratic optimization problem with convex constraints we present locally exact lower bounds and optimali...

We present a parallel implementation of a Lagrangian relaxation algorithm for solving stochastic unit commitment subject to uncertainty in wind power supply and generator and transmission line failures. We present a scenario selection algorithm inspired by importance sampling in order to formulate the stochastic unit commitment problem and validate its performance by comparing it to a stochasti...