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<p>The Whale Optimization Algorithm (WOA) has effectively solved various optimization problems with reasonable results, but it suffers from premature convergence and an imbalanced exploration–exploitation mechanism. To address these shortcomings, this paper presents an Enhanced Whale Optimization Algorithm (EWOA) with three key improvements: (1) adaptive adjustment of the coefficients to manage exploration behavior dynamically, (2) the addition of an inertia weight to ensure stable convergence, and (3) a proposed selection probability parameter to achieve global and exploitation balances. These improvements collectively enhance the algorithm’s convergence speed, accuracy, and resilience. The proposed EWOA is applied to optimize the deployment of Wireless Sensor Networks (WSNs). Various node density simulations prove that EWOA outperforms existing algorithms in terms of F-value, packet delivery ratio, throughput, and computational efficiency.</p>

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An enhanced whale optimization algorithm with inertia weight and dynamic parameter adaptation for wireless sensor network deployment

  • 期刊论文

  • 发表日期：

    2025年7月7日

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  • Qiulin Wu

摘要

The Whale Optimization Algorithm (WOA) has effectively solved various optimization problems with reasonable results, but it suffers from premature convergence and an imbalanced exploration–exploitation mechanism. To address these shortcomings, this paper presents an Enhanced Whale Optimization Algorithm (EWOA) with three key improvements: (1) adaptive adjustment of the coefficients to manage exploration behavior dynamically, (2) the addition of an inertia weight to ensure stable convergence, and (3) a proposed selection probability parameter to achieve global and exploitation balances. These improvements collectively enhance the algorithm’s convergence speed, accuracy, and resilience. The proposed EWOA is applied to optimize the deployment of Wireless Sensor Networks (WSNs). Various node density simulations prove that EWOA outperforms existing algorithms in terms of F-value, packet delivery ratio, throughput, and computational efficiency.