A multi-start variable neighborhood search for solving the single path multicommodity flow problem

Masri, Hatem; Krichen, Saoussen; Guitouni, Adel

doi:10.1016/j.amc.2014.10.123

Cited by 12 publications

(19 citation statements)

References 17 publications

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“…As introduced above, it is NP-hard to find an optimal solution or even to give a constant-factor approximation to the unsplittable flow problem. Thus, the literature investigated various randomized search procedures such as genetic algorithms (Cox 1991;Masri et al 2019), tabu search (Anderson et al 1993;Laguna and Glover 1993;Xu et al 1997), local search and GRASP (Santos et al 2010(Santos et al , 2013aAlvelos and Valério de Carvalho 2007;Masri et al 2015Masri et al , 2019 or ant colony optimization (Li et al 2010;Masri et al 2011). One of the major difficulties encountered when solving the unsplittable flow problem with a meta-heuristic is to efficiently create useful paths for the commodities.…”

Section: Meta-heuristicsmentioning

confidence: 99%

“…In Laguna and Glover (1993) and Masri et al (2015) the k shortest paths are precomputed for each commodity using the algorithm of Yen (1971). The search space of their meta-heuristics is restrained to the space of solutions using only those paths.…”

Section: Meta-heuristicsmentioning

confidence: 99%

“…Indeed, most works use small graphs (less than 50 nodes) on which they manually generate a set of commodities. The largest instances (100 nodes) can be found in the work of Masri et al (2015) and Li et al (2010). Masri et al (2015) use a grid graph while Li et al (2010) create their graphs with an adaptation of the graph generator NETGEN.…”

Section: Instance Datasetsmentioning

confidence: 99%

“…The largest instances (100 nodes) can be found in the work of Masri et al (2015) and Li et al (2010). Masri et al (2015) use a grid graph while Li et al (2010) create their graphs with an adaptation of the graph generator NETGEN. To compensate for this absence of benchmark, we give a detailed explanation of our instance generation procedure.…”

Section: Instance Datasetsmentioning

confidence: 99%

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Randomized rounding algorithms for large scale unsplittable flow problems

et al. 2021

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Unsplittable flow problems cover a wide range of telecommunication and transportation problems and their efficient resolution is key to a number of applications. In this work, we study algorithms that can scale up to large graphs and important numbers of commodities. We present and analyze in detail a heuristic based on the linear relaxation of the problem and randomized rounding. We provide empirical evidence that this approach is competitive with state-of-the-art resolution methods either by its scaling performance or by the quality of its solutions. We provide a variation of the heuristic which has the same approximation factor as the state-of-the-art approximation algorithm. We also derive a tighter analysis for the approximation factor of both the variation and the state-of-the-art algorithm. We introduce a new objective function for the unsplittable flow problem and discuss its differences with the classical congestion objective function. Finally, we discuss the gap in practical performance and theoretical guarantees between all the aforementioned algorithms.

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Section: Meta-heuristicsmentioning

confidence: 99%

Section: Meta-heuristicsmentioning

confidence: 99%

Section: Instance Datasetsmentioning

confidence: 99%

Section: Instance Datasetsmentioning

confidence: 99%

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Randomized rounding algorithms for large scale unsplittable flow problems

et al. 2021

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“…Comprehensive surveys on the approaches to solve multi-commodity flow problems (MCFP) and their variants are provided in [14], [15]. In [16], unsplittable flow and single path MCFPs are studied. Our approach extends this by dealing with the problem of flow variation over time and solves an MCFP as a subproblem.…”

Section: Related Workmentioning

confidence: 99%

Single-path versus multi-path advance reservation in media production networks

Barshan

Moens

Volckaert

et al. 2015

2015 6th International Conference on the Network of the Future (NOF)

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Abstract-In media production, a set of actors works simultaneously on video content from different sources. If the actors are geographically spread, the use of a shared substrate network can improve their collaborative efficiency. In such a network traffic consists mostly of large video files, which need to be transferred respecting strict deadlines. Restrictions on the underlying network can force the use of single-path routing mechanisms over multi-path approaches. In this paper, we investigate the influence of using single-path routing compared to multi-path routing in deadline-aware advance reservation (AR) systems for media production networks. We have modified our previously designed optimal multi-path advance reservation model to incorporate the single-path mechanism and heuristic alternatives are presented and thoroughly evaluated. The experimental results show that the single-path optimal model can only provide satisfactory performance when the network is not in contention. With the heuristic approach, when adequate bandwidth is provided, the multi-path approach outperforms the single-path by up to 7.3%.

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A Novel Greedy Randomized Dynamic Ensemble Selection Algorithm

Rui

Dai

2017

Neural Process Lett

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A multi-start variable neighborhood search for solving the single path multicommodity flow problem

Cited by 12 publications

References 17 publications

Randomized rounding algorithms for large scale unsplittable flow problems

Randomized rounding algorithms for large scale unsplittable flow problems

Single-path versus multi-path advance reservation in media production networks

A Novel Greedy Randomized Dynamic Ensemble Selection Algorithm

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