scholarly journals Binary Search In Linked List

2019 ◽  
Vol 8 (4) ◽  
pp. 2684-2686
Keyword(s):  
Time Complexity ◽  
Binary Search ◽  
Divide And Conquer ◽  
Linear Search ◽  
Linked List

This paper is based on an approach to implement Binary Search in Linked List. Binary Search is divide and conquer approach to search an element from the list of sorted element. In Linked List we can do binary search but it has time complexity O(n) that is same as what we have for linear search which makes Binary Search inefficient to use in Linked List. The main problem that binary search takes O(n) time in Linked List due to fact that in linked list we are not able to do indexing which led traversing of each element in Linked list take O(n) time. In this paper a method is implemented through which binary search can be done with time complexity of O(log2n). This is done with the help of auxiliary array. Auxiliary array helps in indexing of linked list through which one can traverse a node in O(1) complexity hence reducing the complexity of binary search to O(log2n) hence increasing efficiency of binary search in linked

scholarly journals Binary Search In Linked List

2019 ◽  
Vol 9 (1) ◽  
pp. 3151-3153
Keyword(s):  
Time Complexity ◽  
Binary Search ◽  
Divide And Conquer ◽  
Linear Search ◽  
Linked List

This paper is based on an approach to implement Binary Search in Linked List. Binary Search is divide and conquer approach to search an element from the list of sorted element. In Linked List we can do binary search but it has time complexity O(n) that is same as what we have for linear search which makes Binary Search inefficient to use in Linked List. The main problem that binary search takes O(n) time in Linked List due to fact that in linked list we are not able to do indexing which led traversing of each element in Linked list take O(n) time.In this paper a method is implemented through which binary search can be done with time complexity of O(log2n). This is done with the help of auxiliary array. Auxiliary array helps in indexing of linked list through which one can traverse a node in O(1) complexity hence reducing the complexity of binary search to O(log2n) hence increasing efficiency of binary search in linked List.

Pyramid Search: Skip Ring Data Structure-Based New Searching Algorithm

2018 ◽  
Vol 27 (14) ◽  
pp. 1850218
Author(s):  
Mustafa Aksu ◽  
Ali Karcı
Keyword(s):  
Data Structure ◽  
Time Complexity ◽  
Linear Search ◽  
Data Set ◽  
Linked List ◽  
Insertion And Deletion ◽  
Skip List ◽  
Algorithm And Data Structure ◽  
Text Element ◽  
Linked Lists

Our new algorithm and data structure, pyramid search (PS) and skip ring, were created with the help of circular linked list and skip list algorithms and data structures. In circular linked list, operations were performed on a single circular list. Our new data structure consists of circular linked lists formed in layers which were linked in a pyramid way. Time complexity of searching, insertion and deletion algorithms equal to [Formula: see text] (lg[Formula: see text]) in an [Formula: see text]-element skip ring data structure. Therefore, skip ring data structure is employed more effectively ([Formula: see text](lg[Formula: see text])) in circumstances where circular linked lists ([Formula: see text]) are used. The priority is determined based on the searching frequency in PS which was developed in this study. Thus, the time complexity of searching is almost [Formula: see text](1) for [Formula: see text] records data set. In this paper, the applications of searching algorithms like linear search (LS), binary search (BS) and PS were realized and the obtained results were compared. The obtained results demonstrated that the PS algorithm is superior to the BS algorithm.

scholarly journals On Quantum Algorithm for Binary Search and Its Computational Complexity

2015 ◽  
Vol 22 (03) ◽  
pp. 1550019 ◽  
Author(s):  
S. Iriyama ◽  
M. Ohya ◽  
I.V. Volovich
Keyword(s):  
Computational Complexity ◽  
Time Complexity ◽  
Quantum Algorithm ◽  
Binary Search ◽  
Search Problem

A new quantum algorithm for the search problem and its computational complexity are discussed. Its essential part is the use of the so-called chaos amplifier, [8, 9, 10, 13]. It is shown that for the search problem containing [Formula: see text] objects time complexity of the method is polynomial in [Formula: see text].

An Efficient Multibody Divide and Conquer Algorithm

2005 ◽  
Author(s):  
James H. Critchley
Keyword(s):  
Multibody Dynamics ◽  
Time Complexity ◽  
Future Generation ◽  
Parallel Computers ◽  
Parallel Processors ◽  
Divide And Conquer ◽  
Parallel Computer ◽  
Divide And Conquer Algorithm ◽  
Computer Resources ◽  
Theoretical Minimum

A new and efficient form of Featherstone’s multibody Divide and Conquer Algorithm (DCA) is presented. The DCA was the first algorithm to achieve theoretically optimal logarithmic time complexity with a theoretical minimum of parallel computer resources for general problems of multibody dynamics, however the DCA is extremely inefficient in the presence of small to modest parallel computers. The new efficient DCA approach (DCAe) demonstrates that large DCA subsystems can be constructed using fast sequential techniques and realize substantial speed increases in the presence of as few as two parallel processors. Previously the DCA was a tool intended for a future generation of parallel computers, this enhanced version promises practical and competitive performance with the parallel computers of today.

Distributed Operational Space Formulation of Serial Manipulators

2013 ◽  
Vol 9 (2) ◽  
Author(s):  
Kishor D. Bhalerao ◽  
James Critchley ◽  
Denny Oetomo ◽  
Roy Featherstone ◽  
Oussama Khatib
Keyword(s):  
Parallel Algorithms ◽  
Time Complexity ◽  
Degrees Of Freedom ◽  
Null Space ◽  
Divide And Conquer ◽  
Serial Manipulators ◽  
Divide And Conquer Algorithm ◽  
Operational Space ◽  
Space Formulation ◽  
Space Dynamics

This paper presents a new parallel algorithm for the operational space dynamics of unconstrained serial manipulators, which outperforms contemporary sequential and parallel algorithms in the presence of two or more processors. The method employs a hybrid divide and conquer algorithm (DCA) multibody methodology which brings together the best features of the DCA and fast sequential techniques. The method achieves a logarithmic time complexity (O(log(n)) in the number of degrees of freedom (n) for computing the operational space inertia (Λe) of a serial manipulator in presence of O(n) processors. The paper also addresses the efficient sequential and parallel computation of the dynamically consistent generalized inverse (J¯e) of the task Jacobian, the associated null space projection matrix (Ne), and the joint actuator forces (τnull) which only affect the manipulator posture. The sequential algorithms for computing J¯e, Ne, and τnull are of O(n), O(n2), and O(n) computational complexity, respectively, while the corresponding parallel algorithms are of O(log(n)), O(n), and O(log(n)) time complexity in the presence of O(n) processors.

scholarly journals Verifying Time Complexity of Binary Search using Dafny

2021 ◽  
Vol 338 ◽  
pp. 68-81
Author(s):  
Shiri Morshtein ◽  
Ran Ettinger ◽  
Shmuel Tyszberowicz
Keyword(s):  
Time Complexity ◽  
Binary Search

On Parallel Methods of Multibody Dynamics

2003 ◽  
Author(s):  
James H. Critchley ◽  
Kurt S. Anderson
Keyword(s):  
Time Complexity ◽  
Multibody System ◽  
Practical Importance ◽  
Divide And Conquer ◽  
Optimal Time ◽  
Worst Case ◽  
Parallel Methods ◽  
Divide And Conquer Algorithm ◽  
Coordinate Reduction ◽  
Parallel Arrays

Optimal time efficient parallel computation methods for large multibody system dynamics are defined and investigated in detail. Comparative observations are made which demonstrate significant deficiencies in operating regions of practical importance and a new parallel algorithm is generated to address them. The new method of Recursive Coordinate Reduction Parallelism (RCRP) outperforms or directly reduces to the fastest general multibody algorithms available for small parallel resources and obtains “O(logk(n))” time complexity in the presence of larger parallel arrays. Performance of this method relative to the Divide and Conquer Algorithm is illustrated with an operations count for the worst case of a multibody chain system.

Time distribution analysis for binary search of a linked list

1991 ◽  
Vol 23 (4) ◽  
pp. 7-12
Author(s):  
Firooz Khosraviyani ◽  
Mohammad H. Moadab ◽  
Douglas F. Hale
Keyword(s):  
Time Distribution ◽  
Binary Search ◽  
Distribution Analysis ◽  
Linked List

scholarly journals FROM PLANNING TO SEARCHING FOR THE SHORTEST PLAN: AN OPTIMAL TRANSITION

2001 ◽  
Vol 09 (06) ◽  
pp. 827-837 ◽  
Author(s):  
R. TREJO ◽  
J. GALLOWAY ◽  
C. SACHAR ◽  
V. KREINOVICH ◽  
C. BARAL ◽  
...  
Keyword(s):  
Computation Time ◽  
Binary Search ◽  
Planning Problem ◽  
Linear Search ◽  
Worst Case ◽  
Average Complexity ◽  
Case Complexity ◽  
Worst Case Complexity ◽  
Long Time ◽  
Speed Up

If we want to find the shortest plan, then usually, we try plans of length 1, 2, …, until we find the first length for which such a plan exists. When the planning problem is difficult and the shortest plan is of a reasonable length, this linear search can take a long time; to speed up the process, it has been proposed to use binary search instead. Binary search for the value of a certain parameter x is optimal when for each tested value x, we need the same amount of computation time; in planning, the computation time increases with the size of the plan and, as a result, binary search is no longer optimal. We describe an optimal way of combining planning algorithms into a search for the shortest plan – optimal in the sense of worst-case complexity. We also describe an algorithm which is asymptotically optimal in the sense of average complexity.

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