New Hybrid Approach to Solve the 0/1, Bounded Knapsack Problem

Knapsack problem is one of the combinatorial optimization problems, consisting of selecting a subset of given items in such a way that the total profit of the selected items doesn�t exceed the maximum of knapsack capacity. As well known that most of the famous algorithms published nowadays work on either dynamic or greedy system as greedy is a fast technique and dynamic systems can produce an optimal solution for the problem, however, as greedy function can solve the problem with high speed it cannot give an optimal solution and, sometimes, answers are relatively far from optimality. Therefore, the dynamic approach may solve the problem with optimal solution but it consumes much time and space. In order to merge advantages of these two approaches, in this proposed study we introduced an idea that generates a hybrid algorithm that is based on the two methods, the dynamic and the greedy, to get the best performance for finding the best proximity to the optimal solutions