Network failure is categorized into the two types of software and hardware (physical layer) failure. This paper focuses on the physical layer failure in the wireless sensor and actor networks (WSANs). Actors play an important role in data processing, decision-making, and performing appropriate reactions. Single or multiple nodes failure of actors due to the explosion, energy depletion, or harsh environments, can cause multiple disjoint partitions. This paper has proposed a new computational intelligence-based connectivity restoration (CICR) method. It uses a combination of advanced computational intelligence methods to solve restoration problem. The proposed algorithm applies the novel enhanced Lagrangian relaxation with a novel metaheuristic sequential improved grey wolf optimizer (SIGWO) search space algorithm in simultaneous selection of k sponsor and p pathway nodes. The reactive proposed method aims to reduce the travel distance or moving cost and communication cost. As a result, the restored network has minimum of topology change and energy consumption. In terms of total traveled distance, CICR has 37.19%, 71.47%, and 44.71% improvement in the single-node failure averagely in comparison with HCR, HCARE, and CMH, respectively. Also, it has an average of 61.54%, 40.1%, and 57.76% improvement in comparison with DCR, PRACAR, and RTN in multiple partitions resulted from multiple nodes failure, respectively. The reliability of CICR method has improved averagely by 35.85%, 38.46%, 22.03% over HCR, CMH, and HCARE in single-node failure. In multiple nodes failure, reliability of CICR has averagely 61.54% and 20% over DCR and PRACAR, respectively.

网络故障分为软件和硬件（物理层）故障两种类型。本文重点介绍无线传感器和参与者网络（WSAN）中的物理层故障。参与者在数据处理，决策和做出适当反应中起着重要作用。由于爆炸，能量耗尽或恶劣的环境，actor的单节点或多节点故障可能会导致多个不相交的分区。本文提出了一种新的基于计算智能的连接性恢复（CICR）方法。它结合了先进的计算智能方法来解决恢复问题。该算法将新型增强拉格朗日松弛与新型元启发式顺序改进的灰狼优化器（SIGWO）搜索空间算法应用于同步选择的位置。k赞助商和p通路节点。提出的反应性方法旨在减少行进距离或移动成本以及通信成本。结果，恢复的网络具有最小的拓扑变化和能耗。就总的行进距离而言，与HCR，HCARE和CMH相比，CICR的单节点故障平均平均改善了37.19％，71.47％和44.71％。此外，与多个分区的DCR，PRACAR和RTN相比，由于多个节点故障，它分别平均提高了61.54％，40.1％和57.76％。在单节点故障中，CICR方法的可靠性比HCR，CMH和HCARE平均提高了35.85％，38.46％，22.03％。在多节点故障中，CICR的可靠性分别比DCR和PRACAR分别高61.54％和20％。