A hybrid Bee Colony Algorithm by Tabu Search for Multiple Knapsack Problems

In this paper, an enhanced Hybrid artificial bee colony algorithm (HBCT) is proposed to solve combinatorial optimization problems like 0-1 Multidimensional knapsack problem . The aim of MKP is to find a subset of a given set of n objects in such a way that the total profit of the objects included in the subset is maximized, while the total weight of them does not exceed the capacity of the knapsack. Artificial bee colony algorithm is a new swarm intelligence technique inspired by foraging behavior of natural honey bee swarms.The solution search equation of ABC is good in an exploration but is poor inexploitation. So ,in the proposed algorithm first, the harmony search algorithm is used in creating the initial solutions. Thereafter, Tabu search is adopted to avoid falling into local optima.Performance of (HBCT) algorithm on MKP problem instances is compared with the other best heuristic techniques. Computational results show that new (HBCT) algorithm is better in many aspectslike solution quality,convergence which is very rapidly and controls the exploration-exploitation balance.