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Genetic Programming
Published in A Vasuki, Nature-Inspired Optimization Algorithms, 2020
Tree traversal is visiting each node in a tree once. The order in which these nodes are visited leads to three types of traversal known as PreOrder, InOrder, and PostOrder traversals. In PreOrder traversal, the order of visiting nodes is root→leftsubtree→rightsubtree as shown in Figure 5.4. In InOrder traversal, the order of visiting nodes is leftsubtree→root→rightsubtree as shown in Figure 5.5. In PostOrder traversal, the order of visiting nodes is leftsubtree→rightsubtree→root, as shown in Figure 5.6. This is done recursively for all the subtrees until all the nodes of the tree have been visited once.
Structured Chromosome Genetic Algorithms
Published in Ossama Abdelkhalik, Algorithms for Variable-Size Optimization, 2021
Each gene is represented as a node in the chromosome tree. During the crossover and mutation operations, each gene/node in the candidate chromosome tree is visited once. The process of visiting each node in a tree is called tree traversal. One of the simplest ways to implement tree traversal is to use recursive algorithms. However, recursive algorithms incur significant overhead such as the function call stack and memory allocation [34]. Therefore, we switched to an iterative algorithm that uses stacks. However, we found that stack operations such as push and pop introduce significant overhead given that they have to be invoked millions of times. To gain efficiency, we switched to an iterative algorithm that does not involve stacks [34].
Trees
Published in Jonathan L. Gross, Jay Yellen, Mark Anderson, Graph Theory and Its Applications, 2018
Jonathan L. Gross, Jay Yellen, Mark Anderson
A systematic visit of each vertex of a tree is called a tree traversal. Thus, a traversal of a binary tree is a global ordering of its vertices. Four kinds of traversals are presented in this section: level-order, pre-order, post-order, and in-order.
Automated retrieval and comparison of sheet metal parts
Published in International Journal of Computer Integrated Manufacturing, 2023
Yang Yang, Srichand Hinduja, Oladele O Owodunni
In the case of sheet metal parts, most researchers process a boundary representation model to extract features such as a lance, jog, slot, and bead (Kannan and Shunmugam 2009; Yang et al. 2021). These features contain different types of surfaces which are planar, cylindrical, toroidal, conical and/or spherical. Once the features are extracted, the boundary representation model is converted into an attributed tree. A tree representation makes it considerably easier to assess the degree of similarity between two given sheet metal parts. An attributed graph could also be used, but it is not computationally efficient because it is undirected, and traversal can start from any node. But in a rooted tree, traversal starts from the root node, resulting in a unique path, which is obtained at a much smaller effort.
BTLA-LSDG: Blockchain-Based Triune Layered Architecture for Authenticated Subgraph Query Search in Large-Scale Dynamic Graphs
Published in IETE Journal of Research, 2023
G. Sharmila, M. K. Kavitha Devi
Wan et al. [32] attempt to approximate query processing on large-scale knowledge graphs. It is referred to as LKAQ and this scheme is enabled to control the trade-off between in-memory usage and accuracy. In this paper, authors developed two kinds of indexes: M-index and I-index. It is very complex when an approximate query is given. Individual index construction requires more storage space. A balanced multiway multidimensional indexing tree is proposed [33] in the application of Peer-to-Peer (P2P). This index structure is suited for complex query processing. A tree traversal for the adjacency nodes can be in the following: (1). Traverse the first subtree in Inorder, (2). Traverse the node and (3). Traverse the residual subtree in Inorder. Time complexity and space complexity are very large.
An Efficient Document Clustering Approach for Devising Semantic Clusters
Published in Cybernetics and Systems, 2023
E. K. Jasila, N. Saleena, K. A. Abdul Nazeer
The initial centroids are calculated by means of an O (n log n) sorting algorithm based on the Red-Black Tree (RBT) presented by Nazeer, Madhu Kumar, and Sebastian (2011). Even though there are other popular O (n log n) sorting algorithms like heapsort and mergesort, we prefer RBT-based sorting in order to maintain the relative order of duplicate elements and due to space considerations. The Red-Black Tree is a balanced Binary Search tree with faster insertion and removal operations. Because of its relatively relaxed balancing, operations require fewer rotations than the other strictly balanced trees like AVL trees. The insertion operation in a Red-Black Tree requires O (log n) time. Rotation, a local operation in RBT that maintains the Red-Black tree property, is utilized to change the pointer structures. In RBT, both left rotate and right rotate run in a constant amount of time, i.e., O (1). Thereby RBT guarantees a logarithmic bound on primitive operations. The in-order tree traversal gives a listing of the data items in sorted order.