
A Novel Simplified Swarm Optimization for Generalized Reliability Redundancy Allocation Problem
Network systems are commonly used in various fields, such as power grid,...
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Simplified Swarm Optimization for BiObjection Active Reliability Redundancy Allocation Problems
The reliability redundancy allocation problem (RRAP) is a wellknown too...
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Type2 fuzzy reliability redundancy allocation problem and its solution using particle swarm optimization algorithm
In this paper, the fuzzy multiobjective reliability redundancy allocati...
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Novel Algorithm for Computing AllPairs HomogeneityArc BinaryState Undirected Network Reliability
Among various reallife emerging applications, wireless sensor networks,...
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General MultiState Rework Network and Reliability Algorithm
A rework network is a common manufacturing system, in which flows (produ...
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Joint Reliabilityaware and Cost Efficient Path Allocation and VNF Placement using Sharing Scheme
Network function virtualization (NFV) is a vital player of modern networ...
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Allocation of Repetition Redundancy in LoRa
We consider a multipointtopoint network in which sensors periodically ...
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Novel General Active Reliability Redundancy Allocation Problems and Algorithm
The traditional (active) reliability redundancy allocation problem (RRAP) is used to maximize system reliability by determining the redundancy and reliability variables in each subsystem to satisfy the volume, cost, and weight constraints. The RRAP structure is very simple, that is, redundant components are parallel in each subsystem, and all subsystems are either connected in series or in a bridge network. Owing to its important and practical applications, a novel RRAP, called the general RRAP (GRRAP), is proposed to extend the seriesparallel structure or bridge network to a more general network structure. To solve the proposed novel GRRAP, a new algorithm, called the BATSSOA3, used the simplified swarm optimization (SSO) to update solutions, the smallsampling triobjective orthogonal array (SS3OA) to tune the parameters in the proposed algorithm, the binaryadditiontree algorithm (BAT) to calculate the fitness (i.e., reliability) of each solution, and the penalty function to force infeasible back to the feasible region. To validate the proposed algorithm, the BATSSOA3 is compared with stateoftheart algorithms, such as, particle swarm optimization (PSO) and SSO, via designed experiments and computational studies.
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