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The capacitated min-k-cut problem of hypergraphis the problem of partitioning the vertices into k parts, and each part has a different capacity. The objective is to minimize the weight of cut hyper edges. It is an NP-hard problem which is an important problem with extensive applications to many areas, such as VLSI CAD, image segmentation, etc. Although many heuristic algorithms have been developed,...
The shortest path algorithm is the core problems in intelligent transportation system (ITS), especially for the large scale networks. The problem is classically solved by Dijkstra and Floyed algorithm. Meanwhile, many techniques are proposed to improve the algorithms heuristically. In most researches, such techniques are considered individually. In this paper, we propose an improved shortest path...
Automatic service composition has been an active research area in the field of service computing. Service engineers demand algorithms that not only synthesize the correct work plans but also meet the need of the overall qualities like response time, throughput, fee, etc. In this paper, we present a novel QoS-aware approach which adopts a two-phase graph search algorithm. This approach effectively...
Community structure or clustering is ubiquitous in many evolutionary networks including social networks, biological networks and financial market networks. Detecting and tracking community deviations in evolutionary networks can uncover important and interesting behaviors that are latent if we ignore the dynamic information. In biological networks, for example, a small variation in a gene community...
Real-time search is one of the most effective way when an agent can observe only limited information from its environment. RTA*, MTS, and their variations have been proposed as concrete algorithms for real-time search. However, if a heuristic value differs from a real value, an agent with these existing algorithms falls into the ”wrong” state whose heuristic value is small, and the agent might have...
The optimal test point selection is an important problem in testability analysis and diagnosis. In this paper, a new algorithm based on graph-search and multi-attribute decision is proposed. Firstly, A* algorithm is used for graph-search, but when cost functions f(x) of two nodes are equal, three attributes describing a node are introduced, that is, information entropy, the number of un-isolated faults,...
We describe an approach to parallel graph partitioning that scales to hundreds of processors and produces a high solution quality. For example, for many instances from Walshaw's benchmark collection we improve the best known partitioning. We use the well known framework of multi-level graph partitioning. All components are implemented by scalable parallel algorithms. Quality improvements compared...
The problem of path planning deserves a special mention in the field of robotics as it enables the intelligent systems used in autonomous robots to move the robot from one position to the other. Out of the various methods used for solving the problem of robot path planning, two of the common approaches include multi-neuron heuristic search (MNHS) algorithm and evolutionary algorithms (EA). The MNHS...
Planning as heuristic search has proven to be a powerful framework for domain-independent planning. Its effectiveness relies on the heuristic information provided by a state evaluator and the search algorithm used with this in order to solve the problem. This paper presents ordered hill climbing (OHC) search algorithm, which is used as a basis of a heuristic planner in conjunction with FF's relaxed...
For finding the critical path in electrical circuit designs, a shortest-path search must be carried out. This paper introduces a new two-level shortest-path search algorithm specially adapted for parallelization. The proposed algorithm is based on a module-based partitioning algorithm and a shortest-path search parallelized for the usage on multi-core systems. Experimental results show the impact...
The integration of terrain following, terrain avoidance, threat avoidance (TF/TA2) is the key technique for aircrafts to achieve low altitude penetration flight. Depending on this technique, survival ability, accuracy and diversity of aerial assault have been greatly improved. In this paper, the optimal trajectory programming algorithm of TF/TA2 has been improved, and threat avoidance has been studied...
The diagnosis of crop diseases and insect pests depends on the position, pest apparent, and the impact of physiological biochemical and ecological factors, etc., so it is difficult to meet the requirements for the credibility of solving goal by applying a conventional logic-reasoning model. On the basis of the analysis on pests and diseases with hierarchical structure, the fuzzy membership matrix...
In online social networks (OSNs), user connections can be represented as a network. The network formed has distinct properties that distinguish it from other network topologies. In this work, we consider an unstructured keyword based social network topology where each edge has a trust value associated with it to represent the mutual relationship between the corresponding nodes. Users have keywords...
The size of the intermediate results produced while executing queries has a direct impact on query optimizers. Larger size of intermediate results requires more memory usage and more computational power to evaluate their join predicates. Furthermore, if memory size is not big enough, secondary storage will be needed. This paper proposes the Exhaustive Greedy (EG) algorithm to optimize the intermediate...
This paper presents an optimal method based on combination of artificial potential field (APF) and ant colony optimization (ACO) algorithms for global path planning of mobile robots working in partially known environments. Two steps constitute this approach. Firstly, free space model of mobile robot is established by using visible graph method and ACO algorithm is utilized in this model to search...
Recently, it has been suggested that BDD-based RePlanning A* (BDDRPA*), a BDD-based incremental version of A*, might be an efficient search method for solving path-planning problems in artificial intelligence. BDDRPA* combines ideas of BDD-based search and incremental search to repeatedly find shortest paths from a start vertex to a goal vertex while the topology of the graph changes. However, BDDRPA*...
This paper proposes the plateau structure imposed by the Pareto dominance relation as a useful determinant of multiobjective metaheuristic performance. In essence, the dominance relation partitions the search space into a set of equivalence classes, and the probabilities, given a specified neighborhood structure, of moving from one class to another are estimated empirically and used to help assess...
Test points selection for integer-coded fault wise table is a discrete optimization problem. The global minimum set of test points can only be guaranteed by an exhaustive search which is computationally expensive. In this paper, this problem is formulated as a heuristic depth-first graph search problem at first. The graph node expanding method and rules are given. Then, we propose to apply rollout...
In this paper, an incremental subgraph matching problem is introduced as an enhancement to a batched inexact subgraph isomorphism for situation assessment in higher levels of data fusion. The procedure is shown to be a bounded incremental algorithm, meaning that its runtime is a function of the size of the change in the data graph. Solution quality results are shown to be equal to that of TruST with...
Urban traffic situation information is the basis of effective traffic guidance and traffic control. In order to promote communication and practical applications of traffic information, then can provide full, accurate, real time and sufficient traffic information service to public, government and correlative enterprises, in this paper, the authors proposed the dynamic traffic information collection...
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