Mobile Ad Hoc network (MANETS) technology is one of the best to create a network on demand. In MANET environment clustering and routing is an important concern to maintain the stability of the network. The additional overheads in MANETs like scalability, reliability, dynamic nature, bandwidth limitation, and heterogeneous device configuration leads to unstable network environment. In MANET, clustering technique is used to form a group of mobile nodes as a network. In the existing clustering techniques, the parameters are initialized with a predefined value and the performance of a clustering algorithm is totally based on this predefined value, which is considered as the major disadvantage of the existing clustering techniques. Unstable clustering leads to serious performance issues like delay, packet drop, and network disconnection. In this paper, we propose combinatorial optimization algorithm for clustering and routing in MANET using ACO, Black Hole (BH), Fuzzy Set (FS) such as BH-ACO, BH-FUZZY, BH-PSO, BH-COA, BH-LSTM, BH-FS-ACO-LSTM. The proposed algorithm focuses on the areas of clustering on MANET. It reduces delay in cluster formation process. It enables the parameters to adapt the values dynamically. From the experimental results it is clear that the proposed approach is able to achieve the best convergence rate and thus may achieve the best performance.

ACO, Black Hole (BH), Fuzzy Set (FS), LSTM, MANET, Clustering, Load balancing, Routing.