Components Assignment Problem for Multi-Source Multi-Sink Flow Networks with Reliability and Budget Constraints
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TL;DR: In this paper , a genetic-based approach is proposed to solve the components assignment problem under budget constraint, which is based on determining the optimal set of lower boundary points that maximize the system reliability such that the total assignment cost does not exceed the specified budget.
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Abstract: System reliability optimization problem of multi-source multi-sink flow network is defined by searching the optimal components that maximize the reliability and minimize the total assignment cost. Therefore, a genetic-based approach is proposed to solve the components assignment problem under budget constraint. The mathematical model of the optimization problem is presented and solved by the proposed genetic-based approach. The proposed approach is based on determining the optimal set of lower boundary points that maximize the system reliability such that the total assignment cost does not exceed the specified budget. Finally, to evaluate our approach, we applied it to various network examples with different numbers of available components; two-source two-sink network and three-source two-sink network.
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Citations
Multi-objective components assignment problem for multi-source multi-sink flow networks
Noha El den,Mohamed Abdel Aziz,Moatamed Hassan +2 more
TL;DR: In this article , an approach based on random weighted genetic algorithm (RWGA) is proposed to solve the multi-objective components assignment problem (MOCAP) for multi-source multi-sink flow networks when each component has an assignment cost is never discussed.
Solving the Robust Design Problem for MMSFNs Considering Node Failure
01 Dec 2023
TL;DR: Robust design for MMSFNs with node failures is an NP-hard problem. A GA-based approach is proposed to solve this problem. The solution approach is divided into two parts: outer GA and internal GA. The outer GA searches for the optimal capacity of nodes into the minimum-sum network, while the internal GA searches for the best vector with maximum system reliability.
References
Computer network reliability optimization under double-resource assignments subject to a transmission budget
Yi-Kuei Lin,Cheng-Ta Yeh +1 more
TL;DR: An optimization algorithm combining the genetic algorithm, the minimal paths, and the Recursive Sum of Disjoint Products is developed to solve the double-resource assignment problem to maximize network reliability for a computer network.
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Network Reliability of a Time-Based Multistate Network Under Spare Routing With $p$ Minimal Paths
TL;DR: This paper constructs a time-based multistates network composed of multistate edges to study network reliability and evaluates the probability that the given amount of data can be sent through minimal paths simultaneously under both time threshold, and budget constraint.
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Simple algorithms for updating multi-resource allocations in an unreliable flow network
Chung Chi Hsieh,Ming-Hsien Lin +1 more
TL;DR: Algorithms are developed to update the reliability-maximizing resource allocation in an unreliable flow network when either resource demand or the characteristic of the flow network changes, and it is proposed that the updating schemes would perform better than the recomputing scheme in a large sized flow network that transmits various resource types.
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Multistate components assignment problem with optimal network reliability subject to assignment budget
Yi-Kuei Lin,Cheng Ta Yeh +1 more
TL;DR: This paper focuses on solving the multistate components assignment problem to maximize the network reliability under an assignment budget constraint, in which each component has an assignment cost.
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Optimal resource assignment to maximize multistate network reliability for a computer network
Yi-Kuei Lin,Cheng-Ta Yeh +1 more
TL;DR: This paper focuses on the resource assignment problem to propose an efficient approach based on the simple genetic algorithm, in which, a resource assignment is represented as a chromosome and the corresponding multistate network reliability is the fitness value of the chromosome.
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