论文标题
帝国主义竞争算法具有独立性，并限制了解决0-1多维背包问题的同化
Imperialist Competitive Algorithm with Independence and Constrained Assimilation for Solving 0-1 Multidimensional Knapsack Problem
论文作者
论文摘要
多维背包问题是许多现实世界工程应用程序的众所周知的约束优化问题。为了解决这个NP硬性问题，提出了一种新的修改后的帝国主义竞争算法（ICAWICA）。拟议的算法介绍了殖民地独立性的概念，即在经典的ICA同化帝国帝国主义者或人口中任何其他帝国主义的自由意愿。此外，已经实施了一个有限的同化过程，该过程结合了经典的ICA同化和革命运营商，同时保持人口多样性。这项工作调查了101个多维背包问题（MKP）基准实例中提出的算法的性能。实验结果表明，该算法能够在所有小实例中获得最佳解决方案，并为大型MKP实例提供了非常具竞争力的结果。
The multidimensional knapsack problem is a well-known constrained optimization problem with many real-world engineering applications. In order to solve this NP-hard problem, a new modified Imperialist Competitive Algorithm with Constrained Assimilation (ICAwICA) is presented. The proposed algorithm introduces the concept of colony independence, a free will to choose between classical ICA assimilation to empires imperialist or any other imperialist in the population. Furthermore, a constrained assimilation process has been implemented that combines classical ICA assimilation and revolution operators, while maintaining population diversity. This work investigates the performance of the proposed algorithm across 101 Multidimensional Knapsack Problem (MKP) benchmark instances. Experimental results show that the algorithm is able to obtain an optimal solution in all small instances and presents very competitive results for large MKP instances.
