Dynamic robustness analysis of container marine transportation network using improved ACO approach

Third International Workshop on Advanced Computational Intelligence Pub Date : 2010-09-23 DOI:10.1109/IWACI.2010.5585183

G. Tang, Zijian Guo, Xiangqun Song, Wenyuan Wang, Ningning Li

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引用次数: 1

Abstract

The robustness of container marine transportation network (CMTN) has tremendous effects in functioning and security of international shipping and logistics. Therefore, this paper investigates the dynamic robustness of CMTN against random and intentional attacks. We first present a CMTN reconfiguration model for dynamic robustness analysis, which reconfigures a CMTN structure according to types of attacks while minimizing the total cost of CMTN. Secondly an improved Ant Colony Optimization (ACO) is proposed by importing crossover operators into a coarse-grained parallel ACO algorithm to solve the model. Thirdly dynamic robustness of CMTN is defined on the basis of complex network theory. Finally, its application to practical regional CMTN is presented to identify the CMTN robustness using the proposed ACO. The results indicate that the proposed ACO is suitable for solving CMTN problem, and CMTN is a random network but with scale-free characteristics, and better robustness against random and intentional attacks.

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基于改进蚁群算法的集装箱海上运输网络动态鲁棒性分析

集装箱海上运输网络的鲁棒性对国际航运物流的正常运行和安全保障有着重要的影响。因此，本文研究了CMTN对随机攻击和故意攻击的动态鲁棒性。我们首先提出了一个用于动态鲁棒性分析的CMTN重构模型，该模型根据攻击类型对CMTN结构进行重构，同时使CMTN的总成本最小化。其次，提出了一种改进的蚁群算法，将交叉算子引入到粗粒度并行蚁群算法中求解模型。第三，在复杂网络理论的基础上定义了CMTN的动态鲁棒性。最后，将其应用于实际的区域CMTN，利用所提出的蚁群算法来识别CMTN的鲁棒性。结果表明，所提出的蚁群算法适用于求解CMTN问题，CMTN是一个随机网络，但具有无标度特征，对随机攻击和故意攻击具有较好的鲁棒性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Third International Workshop on Advanced Computational Intelligence

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