Opportunistic networks in Internet of Things (IoT) scenario, nodes will have limited time to exchange data and they don't have a pre-established route between them, therefore nodes have to collect the information about IoT network like location of the neighboring nodes and network topology dynamically. These dynamic characteristics pose challenges for routing of data in opportunistic IoT network. Despite multi-copy routing improves delivery probability and reduces number of message retransmission but it suffers from higher latency and overhead due multiple message copies in the network. Hence in this paper, Hybrid Multi-Copy Routing Algorithm (HMCRA) is propounded which classifies potential nodes based on optimal values exhibited by the nodes with respect to energy, speed and distance using fuzzy logic. Genetic Algorithm (GA) is used in fusion with fuzzy logic to form hybrid algorithm in order to obtain optimal route with lesser hop count. The simulation results delineate that the proposed HMCRA algorithm outperforms with respect to delivery probability, hop count, overhead ratio and latency in par with similar multi-copy routing algorithms. The uniqueness of this paper lies in selecting potential nodes and to find optimal path by applying fuzzy logic and GA.