An Improved Binary Chicken Swarm Optimization Algorithm for Solving 0-1 Knapsack Problem

In order to solve the 0-1 knapsack problem, a binary improved chicken swarm optimization algorithm is proposed. Greedy strategy is adapted in chicken swarm optimization to improve the quality of the feasibility. Meanwhile, mutated strategy is adapted in some individuals with low fitness value to increase the population diversity of the algorithm. Numerical experiments are conducted on the 10 0-1 knapsack instances, the simulation results show that the proposed algorithm is superior to particle swarm algorithm and wolf pack algorithm in finding excellent solution, convergence speed and stability.