A Graph Theoretic Approach for Minimizing Storage Space using Bin Packing Heuristics

In the age of Big Data the problem of storing huge volume of data in a minimum storage space by utilizing available resources properly is an open problem and an important research aspect in recent days. This problem has a close relationship with the famous classical NP-Hard combinatorial optimization problem namely the “Bin Packing Problem” where bins represent available storage space and the problem is to store the items or data in minimum number of bins. This research work mainly focuses on to find a near optimal solution of the offline one dimensional Bin Packing Problem based on two heuristics by taking the advantages of graph. Additionally, extreme computational results on some benchmark instances are reported and compared with the best known solution and solution produced by the four other well-known bin oriented heuristics. Also some future directions of the proposed work have been depicted.