Components Assignment Problem for Multi-Source Multi-Sink Flow Networks with Reliability and Budget Constraints
2
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.
read more
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.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
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
A genetic algorithm for the generalised assignment problem
P. C. Chu,John E. Beasley +1 more
TL;DR: Computational results show that the genetic algorithm heuristic is able to find optimal and near optimal solutions that are on average less than 0.01 % from optimality.
567
A simple algorithm for reliability evaluation of a stochastic-flow network with node failure
TL;DR: A simple algorithm is proposed firstly to generate all lower boundary points for d, and then the system reliability can be calculated in terms of such points, and the probability that the maximum flow of the network is not less than d is evaluated.
275
Reliability-oriented multi-resource allocation in a stochastic-flow network
Chung Chi Hsieh,Ming Hsien Lin +1 more
TL;DR: An algorithm for computing the optimal resource allocation at source nodes subject to given resource demands at sink nodes such that the network reliability of the stochastic-flow network is maximized is proposed, and it is proposed that incorporates the principle of minimal path vectors.
54
Evaluation of Optimal Network Reliability Under Components-Assignments Subject to a Transmission Budget
Yi-Kuei Lin,Cheng-Ta Yeh +1 more
TL;DR: The optimal network reliability under components-assignments subject to a transmission budget, in which the transmission cost depends on each component's capacity, is evaluated and an optimization method based on a genetic algorithm is proposed.
41
Reliable and economic resource allocation in an unreliable flow network
Chung Chi Hsieh,Yi-Ting Chen +1 more
TL;DR: An integrated approach is proposed in this study that combines the existing methodologies to determine a reliability-maximizing resource allocation strategy which meets demand at sink nodes and a predetermined transmission cost requirement.
37