Multi-Source Multi-Sink Stochastic-Flow Networks Reliability under Time Constraints

Monsef, Hassan; Abdou, H.

doi:10.17485/ijst/2019/v12i22/144081

Cited by 2 publications

(3 citation statements)

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“…The proposed approach (as required in a GA solution) should include the representation of chromosomes, initial population generation, fitness function, crossover process, and mutation process. Interested readers can refer to [18,25] for details about the GA and its structure, components, and hyperparameters.…”

Section: The Proposed Approachmentioning

confidence: 99%

Robust Design Problem for Multi-Source Multi-Sink Flow Networks Based on Genetic Algorithm Approach

Boubaker,

Radwan,

Refaat Hassan

et al. 2023

Mathematics

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Robust design problems in flow networks involve determining the optimal capacity assignments that enable the network to operate effectively even in the case of events’ occurrence such as arcs or nodes’ failures. Multi-source multi-sink flow networks (MMSFNs) are frequent in many real-life systems such as computer and telecommunication, logistics and supply-chain, and urban traffic. Although numerous studies on the design of MMSFNs have been conducted, the robust design problem for multi-source multi-sink stochastic-flow networks (MMSFNs) remains unexplored. To contribute to this field, this study addresses the robust design problem for MMSFNs using an approach of two steps. First, the problem is mathematically formulated as an optimization problem and second, a sub-optimal solution is proposed based on a genetic algorithm (GA) involving two components. The first component, an outer genetic algorithm, is employed to search the optimal capacity assigned to the network components with minimum sum. The second component, an inner genetic algorithm, is used to find the optimal flow vectors that maximize the system’s reliability. Through extensive experimentation on three different networks with different topologies, the proposed solution has been found to be efficient.

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Section: The Proposed Approachmentioning

confidence: 99%

Robust Design Problem for Multi-Source Multi-Sink Flow Networks Based on Genetic Algorithm Approach

Boubaker,

Radwan,

Refaat Hassan

et al. 2023

Mathematics

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“…Many researchers searched on system reliability in flow network for multicommodity [13][14][15][16][17][18][19][20][21][22][23][24]. Lin [13] proposed an algorithm in terms of minimal paths to generate each lower boundary points in a SFN for a two-commodity demand in which each node and arc have many of capacities and may fail.…”

Section: Introductionmentioning

confidence: 99%

“…Lin [13] proposed an algorithm in terms of minimal paths to generate each lower boundary points in a SFN for a two-commodity demand in which each node and arc have many of capacities and may fail. Hassan and Abdou [14] discussed the reliability evaluation under different conditions, in one of them they studied transmitting multicommodity demand through disjoint path and they proposed an algorithm to evaluate the network reliability for this case. Lin [15] proposed an algorithm to generate each lower boundary points in a SFN of multicommodity demand in the existence of budget constraint to estimate system reliability, in which each node and each arc owns much of possible capacities.…”

Section: Introductionmentioning

confidence: 99%

Maximizing Reliability of Two-Commodity Flow Networks with Time Constraint Using Fuzzy Optimization

Hemeida¹,

Hassan

Hamdy

2022

Aswan University Journal of Sciences and Technology

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The main objective of this paper is to study the optimal components assignment problem for a twocommodity flow network via disjoint minimal paths in the existence of system reliability and total lead-time bands. By using fuzzy membership functions, we formulated the problem as fuzzy linear optimization. An algorithm based on genetic algorithm with fuzzy optimization is suggested for solving the presented problem. The proposed approach achieved success in finding an optimal solution that characterized with maximum reliability and minimum total lead-time. Three studied cases are given four nodes, six nodes and fourteen nodes computer networks to illustrate the efficiency of our proposed approach for solving the presented problem.

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Multi-Source Multi-Sink Stochastic-Flow Networks Reliability under Time Constraints

Cited by 2 publications

References 0 publications

Robust Design Problem for Multi-Source Multi-Sink Flow Networks Based on Genetic Algorithm Approach

Robust Design Problem for Multi-Source Multi-Sink Flow Networks Based on Genetic Algorithm Approach

Maximizing Reliability of Two-Commodity Flow Networks with Time Constraint Using Fuzzy Optimization

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