针对有防御工事的拦截问题的双层模型和采用各种邻域策略的启发式技术

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Abdolsalam Ghaderi, Zahra Hosseinzadeh Bandbon, Anwar Mahmoodi
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引用次数: 0

摘要

供应或服务网络很容易受到人类无意和有意行为以及自然灾害的危害。为确保这些网络中重要基础设施的复原力,需要解决拦截设施的定位问题。目前,不同的攻击者以供应和服务系统为目标,以造成最大程度的破坏。攻击者之间的合作可提高系统漏洞检测的准确性和真实性。本研究探讨了在不同防御系统和异构攻击者的情况下进行拦截定位所面临的挑战。为应对这一挑战,研究人员考虑了一种混合整数非线性双层编程模型。我们采用了启发式优化方法,包括可变邻域搜索、模拟退火和混合可变邻域搜索,以有效解决所建议的模型。我们的研究结果表明,当攻击者合作时,实施各种保护方法会导致系统破坏升级。此外,研究结果还说明了所建议的算法在解决供应或服务网络中拦截位置问题方面的功效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A bi-level model and heuristic techniques with various neighborhood strategies for covering interdiction problem with fortification

A bi-level model and heuristic techniques with various neighborhood strategies for covering interdiction problem with fortification

Supply or service networks are vulnerable to hazards that can stem from both unintentional and intentional human actions, as well as natural calamities. To ensure vital infrastructure resilience in these networks, address the interdiction facility location problem. Currently, diverse groups of attackers target supply and service systems to cause maximum disruption. Collaboration among attackers improves system vulnerability detection accuracy and realism. This research examines the challenges of interdiction location with different defense systems and heterogeneous attackers. To address this challenge, a mixed-integer non-linear bi-level programming model was considered. Heuristic optimization methods including variable neighborhood search, simulated annealing, and hybrid variable neighborhood search are used to efficiently solve the suggested model. The outcomes of our investigation suggest that implementing various protective methods leads to an escalation in system damage when attackers collaborate. Furthermore, the findings illustrate the efficacy of the suggested algorithms in resolving interdiction location issues within supply or service networks.

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来源期刊
Soft Computing
Soft Computing 工程技术-计算机:跨学科应用
CiteScore
8.10
自引率
9.80%
发文量
927
审稿时长
7.3 months
期刊介绍: Soft Computing is dedicated to system solutions based on soft computing techniques. It provides rapid dissemination of important results in soft computing technologies, a fusion of research in evolutionary algorithms and genetic programming, neural science and neural net systems, fuzzy set theory and fuzzy systems, and chaos theory and chaotic systems. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. By linking the ideas and techniques of soft computing with other disciplines, the journal serves as a unifying platform that fosters comparisons, extensions, and new applications. As a result, the journal is an international forum for all scientists and engineers engaged in research and development in this fast growing field.
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