This paper discusses techniques for performing e cient decision-theoretic planning. We give an overview of the drips decisiontheoretic re nement planning system, which uses abstraction to e ciently identify optimal plans. We present techniques for automatically generating search control information, which can signi cantly improve the planner's performance. We evaluate the e ciency of drips both...

Speed and memory requirements of branch and bound algorithms depend on the selection strategy of which candidate node to process next. The goal of this paper is to experimentally investigate this influence to the performance of sequential and parallel branch and bound algorithms. The experiments have been performed solving a number of multidimensional test problems for global optimization. Bran...

In this article we present a parametric branch and bound algorithm for computation of optimal and suboptimal solutions to parametric mixed-integer quadratic programs and parametric mixed-integer linear programs. The algorithm returns an optimal or suboptimal parametric solution with the level of suboptimality requested by the user. An interesting application of the proposed parametric branch an...

This paper addresses a bi-criteria two-machine flowshop scheduling problem when the learning effect is present. The objective is to find a sequence that minimizes a weighted sum of the total completion time and the maximum tardiness. In this article, a branch-and-bound method, incorporating several dominance properties and a lower bound, is presented to search for the exact solution for small j...

User preference queries are very important in spatial databases. With the help of these queries, one can found best location among points saved in database. In many situation users evaluate quality of a location with its distance from its nearest neighbor among a special set of points. There has been less attention about evaluating a location with its distance to nearest neighbors in spatial us...

We present novel branch and bound algorithms for solving Max-SAT and weighted Max-SAT, and provide experimental evidence that outperform the algorithm of Borchers & Furman on Max-2-SAT and weighted Max-2-SAT instances. Our algorithms decrease the time needed to solve an instance, as well as the number of backtracks, up to two orders of magnitude.

A fundamental challenge associated with research or new product development projects is identifying that innovative activity that will deliver success. In such projects, it is typically the case that innovative breakthroughs can be achieved by any of several possible alternative technologies, some of which may fail due to the technological risks involved. In some cases, the project payoff is ob...

State-of-the-art solvers for Constraint Satisfaction Problems (CSP), Mixed Integer Programs (MIP), and satisfiability problems (SAT) are usually based on a branch-and-bound algorithm. The question how to split a problem into subproblems (branching) is in the core of any branch-and-bound algorithm. Branching on individual variables is very common in CSP, MIP, and SAT. The rules, however, which v...

Metric constraints are known to be highly discriminative for many objects, but if training is limited to data captured from a particular 3-D sensor the quantity of training data may be severly limited. In this paper, we show how a crucial aspect of 3-D information–object and feature absolute size–can be added to models learned from commonly available online imagery, without use of any 3-D sensi...

We propose two exact approaches for non-convex quadratic integer minimization subject to linear constraints where lower bounds are computed by considering ellipsoidal relaxations of the feasible set. In the first approach, we intersect the ellipsoids with the feasible linear subspace. In the second approach we penalize exactly the linear constraints. We investigate the connection between both a...