文件名称:FA2
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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.
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.
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FA2.pdf