Efficient heuristics for determining node‐disjoint path pairs visiting specified nodes

Martins, Lucia; Gomes, Teresa; Tipper, David

doi:10.1002/net.21778

Cited by 10 publications

(14 citation statements)

References 31 publications

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“…The benchmark instances in our test consist of three sets. The first set consists of 240 instances generated from 12 networks by randomly selecting must-pass nodes as done in [12]. The second set contains 367 instances provided by Andrade [14].…”

Section: Computational Results and Analysis A Benchmark Instancementioning

confidence: 99%

“…Their algorithm improves the Saksena and Kumar's algorithm, using the k-shortest path algorithm to search for multiple candidate paths between must-pass nodes, but the algorithm does not guarantee that a feasible solution can always be obtained. Martins and Gomes et al [10]- [12] proposed two heuristics for the SSPP-MPN which are Path with Specified Nodes (PSN) and Path with Specified Nodes using Trap Avoidance (PSNTA). The authors pointed out that PSN is more effective than PSNTA for large scale instances.…”

Section: Introductionmentioning

confidence: 99%

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A Multi-Stage Metaheuristic Algorithm for Shortest Simple Path Problem With Must-Pass Nodes

Zhang

2019

IEEE Access

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The shortest simple path problem with must-pass nodes (SSPP-MPN) aims to find a minimumcost simple path in a directed graph, where some specified nodes must be visited. We call these specified nodes as must-pass nodes. The SSPP-MPN has been proven to be NP-hard when the number of specified nodes is more than one, and it is at least as difficult as the traveling salesmen problem (TSP), a well-known NP-hard problem. In this paper, we propose a multi-stage metaheuristic algorithm based on multiple strategies such as k-opt move, candidate path search, conflicting nodes promotion, and connectivity relaxation for solving the SSPP-MPN. The main idea of the proposed algorithm is to transform the problem into classical TSP by relaxing the simple path constraint and try to repair the obtained solutions in order to meet the demands of the original problem. The computational results tested on three sets of totally 863 instances and comparisons with reference algorithms show the efficacy of the proposed algorithm in terms of both solution quality and computational efficiency.INDEX TERMS Constrained shortest path, must-pass nodes, multi-stage metaheuristic algorithm, routing problem, traveling salesman problem.

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Section: Computational Results and Analysis A Benchmark Instancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Multi-Stage Metaheuristic Algorithm for Shortest Simple Path Problem With Must-Pass Nodes

Zhang

2019

IEEE Access

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“…Silva et al [199], Canale et al [47], Sen et al [195], Canale et al [48], Martins et al [141], Ghedini et al [92], Barbosa et al [25], Castillo et al [50], Lin and Zhou [135], and Vass et al [212] analyze problems in survivability, reliability, or fault‐tolerance for different required structures and/or operations. Kucharzak et al [129], Fouquet et al [86], Yang et al [225], Cheng et al [54], Myslitski et al [150], Busing et al [45], and Natalino et al [151] examine novel post‐perturbation routing or path selection protocols.…”

Section: Optimization Models and Network Robustnessmentioning

confidence: 99%

In search of network resilience: An optimization‐based view

et al. 2020

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Fifty years of research in Networks coincides with 50 years of advances in resilience theory and applications. The purpose of this review is to identify how these two technical communities influenced each other in the past and can bolster each other in the future. Advances in resilience theory show that there are at least four ways networks demonstrate resilience: robustness, rebound, extensibility, and adaptability. Research published in Networks and by the broader network optimization community has focused primarily on technical methods for robustness and rebound. We review this literature to organize seminal problems and papers on the ability of networks to manage increasing stressors and return to normal activities after a stressful event. In contrast, the Networks community has made less progress addressing issues for network extensibility and adaptability. Extensibility refers to the ability to stretch current operations to surprising situations and adaptability refers to the ability to sustain operations into the future. We discuss ways to harness existing network optimization methods to study these forms of resilience and outline their limitations. We conclude by providing a research agenda that ensures the Networks community remains central to future advances in resilience while being pragmatic about the limitations of network optimization for achieving this task.

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“…It solved the SRLG disjoint path pair problem by introducing a Modified Bhandari's edge‐disjoint shortest path pair Heuristic (MBH) and using the Modified Suurballe's Heuristic (MSH). To improve survivability furthermore, Martins et al modified heuristic alogrithm to protect the calculated path by a node‐disjoint backup path in 2017. Although it could generate a significant number of optimal solutions, it did not discuss the optimality of the obtained solutions.…”

Section: Related Workmentioning

confidence: 99%

An efficient Manhattan‐distance‐constrained disjoint paths algorithm for incomplete mesh network

Zhao

Wang

Xiong

et al. 2018

Concurrency and Computation

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Finding link/node-disjoint paths between a pair of nodes is capable of providing Quality of Service and reliable routing which is very critical for mesh-connected Network-on-Chip. State-of-art works usually aim at random topologies and multiple constraints. Therefore, it is difficult to optimize their time complexity. In this paper, MDPPIM (Manhattan-distance-constrained Disjoint Path Pair Problem in Incomplete Mesh) problem is presented based on Network-on-Chip application scenarios. Then, PCDP (Path-Counting Disjoint Path) algorithm is proposed to solve the MDPPIM problem with low time complexity. Compared with previous disjoint path algorithms, PCDP algorithm does not have to use Dijkstra's algorithm to find a shortest path. It is optimized according to the feature of incomplete mesh such as the regularity of mesh and Manhattan-distance constraint. Therefore, it is with low time complexity. Numerical results demonstrate the proposed PCDP algorithm's effectiveness and low time complexity.

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Efficient heuristics for determining node‐disjoint path pairs visiting specified nodes

Cited by 10 publications

References 31 publications

A Multi-Stage Metaheuristic Algorithm for Shortest Simple Path Problem With Must-Pass Nodes

A Multi-Stage Metaheuristic Algorithm for Shortest Simple Path Problem With Must-Pass Nodes

In search of network resilience: An optimization‐based view

An efficient Manhattan‐distance‐constrained disjoint paths algorithm for incomplete mesh network

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