The global consumption of sh products is increasing on the scale of millions of tonnes every year. This makes the aquaculture industry as one of the leading sectors to provide food, employment, and ensuring a sustainable livelihood. The implication of rapid growth in global sh production and massive consumption is causing productivity burden on the sheries management to meet the market demands. This eventually leads to aggravated competition within the shing networked community. For surviving the competition and increased pressure, few people from shing community often indulge in various kinds of illegal shing activities. Illegal, Unreported and Unregulated (IUU) shing happens to be a major problem plaguing the sh production. Our research proposes a solution based on o cial transhipment station that solves the problems of illegal transhipment activities, thereby allowing transhipment to continue in a legal and safe manner. We have proposed Cost Optimisation Based Adaptive clustering (COBAC) algorithm that takes into consideration various operational cost and provides the location of establishment of the wirelessly operating transhipment stations in the ocean. The performance of the proposed transhipment was compared with random, greedy and heuristic approaches. Also, the experimentation results show that our proposed COBAC algorithm consumes one-tenth execution time as compared to Brute force clustering and produced result with 0.1% relative error.