In previous work, we, and also Epperly and Pistikopoulos, proposed an analysis of general nonlinear programs that identified certain variables as convex, not ever needing subdivision, and non-convex, or possibly needi...
详细信息
In previous work, we, and also Epperly and Pistikopoulos, proposed an analysis of general nonlinear programs that identified certain variables as convex, not ever needing subdivision, and non-convex, or possibly needing subdivision in branch and bound algorithms. We proposed a specific algorithm, based on a generated computational graph of the problem, for identifying such variables. In our previous work, we identified only independent variables in the computational graph. Here, we examine alternative sets of non-convex variables consisting not just of independent variables, but of a possibly smaller number of intermediate variables. We do so with examples and theorems. We also apply variants of our proposed analysis to the well-known COCONUT Lib-1 test set. If the number of such non-convex variables is sufficiently small, it may be possible to fully subdivide them before analysis of ranges of objective and constraints, thus dispensing totally with the branch and bound process. Advantages to such a non-adaptive process include higher predictability and easier parallizability. We present an algorithm and exploratory results here, with a more complete empirical study in a subsequent paper.
In previous work, we, and also Epperly and Pistikopoulos, proposed an analysis of general nonlinear programs that identified certain variables as convex, not ever needing subdivision, and non-convex, or possibly needi...
详细信息
In previous work, we, and also Epperly and Pistikopoulos, proposed an analysis of general nonlinear programs that identified certain variables as convex, not ever needing subdivision, and non-convex, or possibly needing subdivision in branch and bound algorithms. We proposed a specific algorithm, based on a generated computational graph of the problem, for identifying such variables. In our previous work, we identified only independent variables in the computational graph. Here, we examine alternative sets of non-convex variables consisting not just of independent variables, but of a possibly smaller number of intermediate variables. We do so with examples and theorems. We also apply variants of our proposed analysis to the well-known COCONUT Lib-1 test set. If the number of such non-convex variables is sufficiently small, it may be possible to fully subdivide them before analysis of ranges of objective and constraints, thus dispensing totally with the branch and bound process. Advantages to such a non-adaptive process include higher predictability and easier parallizability. We present an algorithm and exploratory results here, with a more complete empirical study in a subsequent paper.
We propose a new and efficient method for 3D object localization and fine-grained 3D pose estimation from a single 2D image. Our approach follows the classical paradigm of matching a 3D model to the 2D observations. O...
详细信息
ISBN:
(纸本)9781479930227
We propose a new and efficient method for 3D object localization and fine-grained 3D pose estimation from a single 2D image. Our approach follows the classical paradigm of matching a 3D model to the 2D observations. Our first contribution is a 3D object model composed of a set of 3D edge primitives learned from 2D object blueprints, which can be viewed as a 3D generalization of HOG features. This model is used to define a matching cost obtained by applying a rigid-body transformation to the 3D object model, projecting it onto the image plane, and matching the projected model to HOG features extracted from the input image. Our second contribution is a very efficient branch-and-bound algorithm for finding the 3D pose that maximizes the matching score. For this, 3D integral images of quantized HOGs are employed to evaluate in constant time the maximum attainable matching scores of individual model primitives. We applied our method to three different datasets of cars and achieved promising results with testing times as low as less than half a second.
Usual techniques to solve WCSP are based on cost transfer operations coupled with a branch and bound algorithm. In this paper, we focus on an approach integrating extraction and relaxation of Minimal Unsatisfiable Cor...
详细信息
ISBN:
(纸本)9781479929719
Usual techniques to solve WCSP are based on cost transfer operations coupled with a branch and bound algorithm. In this paper, we focus on an approach integrating extraction and relaxation of Minimal Unsatisfiable Cores in order to solve this problem. We derive our approach in two ways: an incomplete, greedy, algorithm and a complete one.
In this paper we propose an approach to jointly infer the room layout as well as the objects present in the scene. Towards this goal, we propose a branch and bound algorithm which is guaranteed to retrieve the global ...
详细信息
ISBN:
(纸本)9781479928392
In this paper we propose an approach to jointly infer the room layout as well as the objects present in the scene. Towards this goal, we propose a branch and bound algorithm which is guaranteed to retrieve the global optimum of the joint problem. The main difficulty resides in taking into account occlusion in order to not over-count the evidence. We introduce a new decomposition method, which generalizes integral geometry to triangular shapes, and allows us to bound the different terms in constant time. We exploit both geometric cues and object detectors as image features and show large improvements in 2D and 3D object detection over state-of-the-art deformable part-based models.
In transportation networks the robustness of a network regarding nodes and links failures is a key factor for its design. At the same time, traveling passengers usually prefer the itinerary with fewer legs. The averag...
详细信息
ISBN:
(纸本)9781479901890
In transportation networks the robustness of a network regarding nodes and links failures is a key factor for its design. At the same time, traveling passengers usually prefer the itinerary with fewer legs. The average clustering coefficient can be used to measure the robustness of a network. A high average clustering coefficient is often synonymous with a lower average travel distance and fewer number of legs. In this paper we present the average weighted clustering coefficient maximization problem, and give several solution methods based on branch and bound algorithm, dynamic programming and quadratically constrained programs.
Based on the distributed energy technology, MicroGrid has caused wide attention. It is of great significance to solve the problem of electricity generation in rural areas by establishing an independent MicroGrid syste...
详细信息
ISBN:
(纸本)9781629936017
Based on the distributed energy technology, MicroGrid has caused wide attention. It is of great significance to solve the problem of electricity generation in rural areas by establishing an independent MicroGrid system, which mainly consists of solar energy and wind energy. It becomes crucial to find a way to optimize the structure of MicroGrid according to various energy situations. Based on the analysis of the general structure and operation modes of MicroGrid, a hybrid power model, which containing photovoltaic power system (PV), wind power system (WT) and energy storage battery (BATT), has been established in this article. The optimization model and corresponding calculation method not only provide an innovative research method, but also contribute to the further research and application on design methods and operation modes of the distributed MicroGrid system. According to the model established in the article, a MicroGrid system of a village scale has been analysed as an example. With the help of MATLAB Software, the branch and bound algorithm is used in order to minimize the cost of MicroGrid. The optimal installed capacity of PV, WT and BATT is presented. The generating cost per kWh and power supply reliability are demonstrated in this article as well.
This paper proposes new machine based lower bounds for scheduling the flowshop with blocking constraints problem while minimizing the total tardiness and total weighted tardiness. Some characteristics of the developed...
详细信息
ISBN:
(纸本)9781479903146
This paper proposes new machine based lower bounds for scheduling the flowshop with blocking constraints problem while minimizing the total tardiness and total weighted tardiness. Some characteristics of the developed branch and bound algorithm are discussed and computational experiments on several random instances are presented. The obtained results compare favorably with previous works in the litterature.
Attack graph is a popular tool for modelling multi-staged, correlated attacks on computer networks. Attack graphs have been widely used for measuring network security risks. Majority of the works on attack graph use h...
详细信息
Attack graph is a popular tool for modelling multi-staged, correlated attacks on computer networks. Attack graphs have been widely used for measuring network security risks. Majority of the works on attack graph use host-based or state-based approaches. These attack graph models are either too restrictive or too resource consuming. Also, a significant portion of these works have used 'probability of successfully exploiting a network' as the metric. This approach requires that the 'probability of successfully exploiting individual vulnerabilities' be known a priori. Finding such probabilities is inherently difficult. This present study uses exploit dependency graph, which is a space efficient and expressive attack graph model. It also associates an additive cost with executing individual exploits, and defines a security metric in terms of the 'minimum cost required to successfully exploit the network'. The problem of calculating the said metric is proved to be NP-complete. A modified depth first branch and bound algorithm has been described for calculating it. This study also formulates, a linear-time computable, security metric in terms of the 'expected cost required to successfully exploit the network' assuming a random attacker model and an uncorrelated attack graph.
This paper presents a branch, bound, and Remember (BB&R) exact algorithm using the Cyclic Best First Search (CBFS) exploration strategy for solving the scheduling problem, a single machine scheduling problem with ...
详细信息
This paper presents a branch, bound, and Remember (BB&R) exact algorithm using the Cyclic Best First Search (CBFS) exploration strategy for solving the scheduling problem, a single machine scheduling problem with sequence dependent setup times where the objective is to find a schedule with minimum total tardiness. The BB&R algorithm incorporates memory-based dominance rules to reduce the solution search space. The algorithm creates schedules in the reverse direction for problems where fewer than half the jobs are expected to be tardy. In addition, a branch and bound algorithm is used to efficiently compute tighter lower bounds for the problem. This paper also presents a counterexample for a previously reported exact algorithm in Luo and Chu (Appl Math Comput 183(1):575-588, 2006) and Luo et al. (Int J Prod Res 44(17):3367-3378, 2006). Computational experiments demonstrate that the algorithm is two orders of magnitude faster than the fastest exact algorithm that has appeared in the literature. Computational experiments on two sets of benchmark problems demonstrate that the CBFS search exploration strategy can be used as an effective heuristic on problems that are too large to solve to optimality.
暂无评论