一种改进的萤火虫算法解决动态0-1背包问题。经过测试，算法就有良好的性能。-Firefly Algorithm (FA), Genetic Algorithm (GA) and Differential

Evolution (DE) have been widely used for static optimization problems, but the applications of those

algorithms in dynamic environments are relatively lacking. In the present study, an effective FA introducing

diversity with partial random restarts and with an adaptive move procedure is developed and proposed

for solving dynamic multidimensional knapsack problems. To the best of our knowledge this

paper constitutes the first study on the performance of FA on a dynamic combinatorial problem. In order

to　uate the performance of the proposed algorithm the same problem is also modeled and solved by

GA, DE and original FA. Based on the computational results and convergence capabilities we concluded

that improved FA is a very powerful algorithm for solving the multidimensional knapsack problems

for both static and dynamic environments.