Aiming at the shortcoming that the traditional binary swarm intelligent algorithm easily falls into local optimum and has slow convergence speed when solving the 0-1 knapsack problem,a new binary lion  warm optimization algorithm (BLSO) is proposed to solve the discrete space problem.The BLSO algorithm redefines the positions of the lion, lioness and cubs, and introduces the inverse operator, move operator and learning operator to construct a brand-new location transfer method and the local search rule.The greedy strategy is added to make the solution feasible and fully utilized, so as to enhance the local search ability and speed up the convergence. The simulation experiments of nine typical 0-1 knapsack cases show that the proposed algorithm can not only solve the 0-1 knapsack problem effectively, but also search for suboptimal solutions with higher precision and even global optimal solutions quickly. The solutions have strong stability. When solving high-dimensional 0-1 knapsack problems, the proposed algorithm is superior to the reference algorithm in terms of optimization time and precision.

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