Pan JS, Zhang SQ, Chu SC, Yang HM, Yan B.
Willow Catkin Optimization Algorithm Applied in the TDOA-FDOA Joint Location Problem.
Entropy (Basel) 2023;
25:171. [PMID:
36673312 PMCID:
PMC9858194 DOI:
10.3390/e25010171]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 01/06/2023] [Accepted: 01/11/2023] [Indexed: 06/17/2023]
Abstract
The heuristic optimization algorithm is a popular optimization method for solving optimization problems. A novel meta-heuristic algorithm was proposed in this paper, which is called the Willow Catkin Optimization (WCO) algorithm. It mainly consists of two processes: spreading seeds and aggregating seeds. In the first process, WCO tries to make the seeds explore the solution space to find the local optimal solutions. In the second process, it works to develop each optimal local solution and find the optimal global solution. In the experimental section, the performance of WCO is tested with 30 test functions from CEC 2017. WCO was applied in the Time Difference of Arrival and Frequency Difference of Arrival (TDOA-FDOA) co-localization problem of moving nodes in Wireless Sensor Networks (WSNs). Experimental results show the performance and applicability of the WCO algorithm.
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