scholarly journals Corrigendum to “A parallel compact cuckoo search algorithm for three-dimensional path planning” [Appl. Soft Comput. 94 (2020) 106443]

2022 ◽  
Vol 114 ◽  
pp. 106710
Author(s):  
Pei-Cheng Song ◽  
Jeng-Shyang Pan ◽  
Shu-Chuan Chu
Keyword(s):  
Path Planning ◽  
Search Algorithm ◽  
Three Dimensional ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm

scholarly journals Optimized cuckoo search algorithm using tournament selection function for robot path planning

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142199613
Author(s):  
Kaushlendra Sharma ◽  
Shikha Singh ◽  
Rajesh Doriya
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Selection Function ◽  
Local Minima ◽  
Robot Path Planning ◽  
Tournament Selection ◽  
Robot Path

Acceptability of mobile robots in various applications has led to an increase in mobile robots’ research areas. Path planning is one of the core areas which needs to be improvised at a higher level. Optimization is playing a more prominent role these days. The nature-inspired algorithm is contributing to a greater extent in achieving optimization. This article presents the modified cuckoo search algorithm using tournament selection function for robot path planning. Path length and Path time are the algorithm’s parameters to validate the effectiveness and acceptability of the output. The cuckoo search algorithm’s fundamental working principle is taken as the baseline, and the tournament selection function is adapted to calculate the optimum path for robots while navigating from its initial position to final position. The tournament selection function is replacing the concept of random selection done by the cuckoo search algorithm. The use of tournament selection overcomes local minima for robots while traversing in the configuration space and increases the probability of giving more optimum results. The conventional cuckoo search algorithm whose random selection mechanism may lead to premature convergence may fall into the local minima. The use of tournament selection function increases the probability of giving better results as it allows all the possible solution to take part in the tournament. The results are analysed and compared with other relevant work like cuckoo search algorithm and particle swarm optimization technique and presented in the article. The proposed method produced a better output in terms of path length and path time.

scholarly journals An Improved Three-dimensional DV-Hop Localization Algorithm Optimized by Adaptive Cuckoo Search Algorithm

2017 ◽  
Vol 13 (02) ◽  
pp. 102 ◽  
Author(s):  
Lieping Zhang ◽  
Fei Peng ◽  
Peng Cao ◽  
Wenjun Ji
Keyword(s):  
Search Algorithm ◽  
Three Dimensional ◽  
Cuckoo Search ◽  
Adaptive Strategy ◽  
Cuckoo Search Algorithm ◽  
Position Estimation ◽  
Localization Algorithm ◽  
Node Localization ◽  
Localization Accuracy ◽  
Unknown Node

Aiming at the low accuracy of DV-Hop localization algorithm in three-dimensional localization of wireless sensor network, a DV-Hop localization algorithm optimized by adaptive cuckoo search algorithm was proposed in this paper. Firstly, an improved DV-Hop algorithm was proposed, which can reduce the localization error of DV-Hop algorithm by controlling the network topology and improving the method for calculating average hop distance. Meanwhile, aiming at the slow convergence in traditional cuckoo search algorithm, the adaptive strategy was improved for the step search strategy and the bird's nest recycling strategy. And the adaptive cuckoo search algorithm was introduced to the process of node localization to optimize the unknown node position estimation. The experiment results show that compared with the improved DV-Hop algorithm and the traditional DV-Hop algorithm, the DV-Hop algorithm optimized by adaptive cuckoo search algorithm improved the localization accuracy and reduced the localization errors.

scholarly journals Path Planning Optimization for Agricultural Spraying Robots Using Hybrid Dragonfly – Cuckoo Search Algorithm

2021 ◽  
Vol 36 (1) ◽  
pp. 412-419
Author(s):  
S. Muthukumaran ◽  
Manikandan Ganesan ◽  
J. Dhanasekar ◽  
Ganesh Babu Loganathan
Keyword(s):  
Path Planning ◽  
Agricultural Landscape ◽  
Search Algorithm ◽  
Travelling Salesman Problem ◽  
Research Work ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Computational Techniques ◽  
Solution Quality ◽  
Routing Problem

Finding collision-free paths and optimized path coverage over an agricultural landscape has been a critical research problem among scientists and researchers over the years. Key precision farming strategies such as seeding, spraying fertilizers, and harvesting require special path planning techniques for efficient operations and will directly influence reducing the running cost of the farm. The main objective of this research work is to generate an optimized sequential route in an agricultural landscape with the nominal distance. In this proposed work, a novel Hybrid Dragonfly – Cuckoo Search algorithm is proposed and implemented to generate the sequential route for achieving spraying applications in greenhouse environments. Here the agricultural routing problem is expressed as a Travelling Salesman Problem, and the simulations are performed to find the effectiveness of the proposed algorithm. The proposed algorithm has generated better results when compared with other computational techniques such as PSO in terms of both solution quality and computational efficiency.

Sign in / Sign up

Export Citation Format

Share Document