核加速萤火虫算法求解有界背包问题

Core Accelerated Firefly Algorithm for Solving Bounded Knapsack Problem

针对有界背包问题,本文提出一种结合核算法的改进萤火虫算法.首先采用核算法对问题规模进行缩减,为了使算法更适于不同规模的有界背包问题,根据规模对核半径进行自适应控制,对缩减后的剩余物品利用基于Levy飞行的萤火虫算法进行位置更新,并对更新后的最优个体进行变异操作以此增加种群多样性.通过仿真实验表明新改进算法能有效求解有界背包问题.

In order to solve the bounded knapsack problem,an improved firefly algorithm combined with core algorithm is proposed.First using the core algorithm to reduce the scale of the problem,in order to make the algorithm more suitable for different sizes of bounded knapsack problem,According to the size of the problem,the nuclear radius is adaptively controlled to obtain the remaining items,and the remaining items were updated with the firefly algorithm based on Levy flight,the updated optimal individuals were mutated to increase the diversity of the population.Simulation results show that the improved algorithm can effectively solve bounded knapsack problem.