A binary firefly algorithm for knapsack problems

Knapsack problems are one of the classical NP-hard problem and it offers many practical applications in vast field of different areas. Several traditional as well as population based metaheuristic algorithms are applied to solve this problem. In this paper, we introduce the binary version of firefly algorithm (FA) for solving knapsack problems, specially 01 knapsack problem. The modified algorithm utilizes the advantages of the variable distance move along with the opposition-based learning mechanism to solve knapsack problems efficiently. So far FA is generally applied to continuous optimization problems. In order to investigate the performance of FA on combinatorial optimization problem, an attempt is made in this paper. To demonstrate the efficiency of the proposed algorithm an extensive computational study is provided with standard bench mark problem instances and comparison with particle swarm optimization is also carried out.