CICDWOA: A Collective Cognitive Sharing Whale Optimization Algorithm with Cauchy Inverse Cumulative Distribution for 2D/3D Path Planning and Engineering Design Problems
Junhao Wei, Yanxiao Li, Seyedali Mirjalili, Dexing Yao, Yifu Zhao, Haochen Li, Xudong Ye, Zikun Li, Qingyang Xu, Baili Lu, Ngai Cheong, Dengcheng Yang, Sio-Kei Im, Yapeng Wang, Xu Yang

TL;DR
CICDWOA is an advanced whale optimization algorithm that incorporates collective cognitive sharing, Cauchy distribution, and hybrid mutation strategies to improve convergence speed, accuracy, and robustness in complex 2D/3D path planning and engineering design problems.
Contribution
This paper introduces CICDWOA, a novel WOA variant with new initialization, sharing, and updating mechanisms, enhancing global exploration and local exploitation capabilities.
Findings
Outperforms classical WOA and other metaheuristics in benchmark tests.
Achieves faster convergence and higher accuracy in path planning.
Effectively solves complex engineering design problems.
Abstract
The Whale Optimization Algorithm (WOA) has shown strong optimization ability but still suffers from premature convergence and weak search diversity. To address these issues, this paper proposes an enhanced WOA variant called CICDWOA. The proposed algorithm introduces a Good Nodes Set (GNS) method for uniform population initialization, a Collective Cognitive Sharing (CCS) mechanism to enhance group collaboration, and an Enhanced Spiral Updating strategy based on the Cauchy Inverse Cumulative Distribution (CICD) to strengthen global exploration and local exploitation balance. In addition, a nonlinear convergence factor and a Hybrid Gaussian-Cauchy mutation based on Differential Evolution (DE) further improve convergence efficiency and population diversity. CICDWOA was evaluated on 23 benchmark functions, 2D robot path planning problems, 3D UAV path planning tasks and 10 engineering design…
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Taxonomy
TopicsRobotic Path Planning Algorithms · Metaheuristic Optimization Algorithms Research · Vehicle Routing Optimization Methods
