Breadth-first heuristic search

Zhou, Rong; Hansen, Eric A.

doi:10.1016/j.artint.2005.12.002

Cited by 159 publications

(124 citation statements)

References 14 publications

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“…But the problem of DFS is, it normally searches by moving forward but not by considering cost. We also analysis breadth first search algorithm [14] and heuristic search [13] algorithm to get out expected result. To get the optimized cost base solution, we analysis Dijkstra's Algorithm [14].…”

Section: Related Workmentioning

confidence: 99%

Intelligent Tour Planning System using Crowd Sourced Data

Miah¹,

Masuduzzaman²,

Sarkar³

et al. 2018

IJEME

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To observe the beauty of nature and to visit various places around the world, a vast number of tourists visit different countries and many tourist attraction sites now-a-days. But Most of the tourist places have failed to introduce itself as a tourist destination to the visitor due to lack of proper information and proper guideline to visit there. This paper tries to focus on some problems in the tourism industry and try to solve those problems using crowd sourced data with some customized algorithms. Some of the main problems are the lack of information about a destination tourist spot, combination on budget to visit the spot, time of travels etc. We proposed a customize algorithm which will provide maximum suggestion to visit a place with nearest all sub place based on user destination within their given budget and time. Using our method, user can choose the most suitable plan for them to visit those places.

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Section: Related Workmentioning

confidence: 99%

Intelligent Tour Planning System using Crowd Sourced Data

Miah¹,

Masuduzzaman²,

Sarkar³

et al. 2018

IJEME

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“…The Breadth First BnB approach is related to Breadth-First Heuristic Search (BFHS) [26], a frontier search method that was designed to save internal memory. It is based on the observation that the Breadth First Search frontier is often much smaller than the best-first search frontier.…”

Section: Resultsmentioning

confidence: 99%

“…The crucial complexity parameter is the locality or duplicate elimination scope as defined in [26], which defines the number of previous levels to be considered. In the text, this notion of locality for an automaton A is referred to as locality(A).…”

Section: External Search In Real-time Systemsmentioning

confidence: 99%

Real-Time Model Checking on Secondary Storage

Edelkamp

Jabbar

Model Checking and Artificial Intelligence

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Abstract. In this paper, we consider disk based exploration in priced timed automata for resource-optimal scheduling. State spaces for large problems can easily go beyond the main memory capacity. We propose the use of hard disk to store the generated state space induced by priced timed automata. We contribute three algorithms: External Breadth First Search for reachability analysis in ordinary timed automata, External Breadth First Branch-and-Bound for cost-optimal reachability analysis in priced timed automata, and Iterative Broadening External Breadth First Branch-and-Bound for a partial exploration in priced timed automata. The third algorithm achieves its completeness by trying to find an upper bound on the optimal solution in an incomplete search tree. Iteratively, the upper bound is made tighter and the coverage of the search space is widened. We present correctness and completeness proofs for the suggested algorithms along with experimental results on different instances of aircraft landing scheduling to validate the practicality of our approach.

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“…Both of these methods are readily applicable to P-FBFT-DDD EM . Zhou and Hansen [17] outline a method for using a breadthfirst traversal algorithm to mimick the A* algorithm [5] in graphs featuring uniform cost edges. Their method is also readily applicable to P-FBFT-DDD EM .…”

Section: Related Workmentioning

confidence: 99%

A Parallel External-Memory Frontier Breadth-First Traversal Algorithm for Clusters of Workstations

Niewiadomski

Amaral

Holte

2006 International Conference on Parallel Processing (ICPP'06)

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Abstract-This paper presents a parallel external-memory algorithm for performing a breadth-first traversal of an implicit graph on a cluster of workstations. The algorithm is a parallel version of the sorting-based external-memory frontier breadthfirst traversal with delayed duplicate detection algorithm. The algorithm distributes the workload according to intervals that are computed at runtime via a sampling-based process. We present an experimental evaluation of the algorithm where we compare its performance to that of its sequential counterpart on the implicit graphs of two classic planning problems. The speedups attained by the algorithm over its sequential counterpart are consistently near linear and frequently above linear. Analysis reveals that the algorithm is proficient at distributing the workload and that increasing the number of samples obtained by the sampling-based process improves workload distribution. Analysis also reveals that the algorithm benefits from the caching of external memory in internal memory that is done by the operating system.

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Breadth-first heuristic search

Cited by 159 publications

References 14 publications

Intelligent Tour Planning System using Crowd Sourced Data

Intelligent Tour Planning System using Crowd Sourced Data

Real-Time Model Checking on Secondary Storage

A Parallel External-Memory Frontier Breadth-First Traversal Algorithm for Clusters of Workstations

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