Lower bounds on two-terminal network reliability
Discrete Applied Mathematics
Computers and Operations Research
A genetic algorithm for distributed system topology design
Computers and Industrial Engineering - Collection of papers on Computer-Integrated Manufacturing
An updated survey of GA-based multiobjective optimization techniques
ACM Computing Surveys (CSUR)
Estimation of all-terminal network reliability using an artificial neural network
Computers and Operations Research
Evolutionary Algorithms for Multi-Objective Optimization: Performance Assessments and Comparisons
Artificial Intelligence Review
Integrating Heuristic Knowledge and Optimization Models for Communication Network Design
IEEE Transactions on Knowledge and Data Engineering
A Genetic Algorithm for Survivable Network Design
Proceedings of the 5th International Conference on Genetic Algorithms
Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art
Evolutionary Computation
An overview of evolutionary algorithms in multiobjective optimization
Evolutionary Computation
Multi-objective genetic algorithms: Problem difficulties and construction of test problems
Evolutionary Computation
Strong Formulations for 2-Node-Connected Steiner Network Problems
COCOA 2008 Proceedings of the 2nd international conference on Combinatorial Optimization and Applications
Computers and Operations Research
Meta-Modeling in Multiobjective Optimization
Multiobjective Optimization
Computers and Electrical Engineering
A new ILP formulation for 2-root-connected prize-collecting Steiner networks
ESA'07 Proceedings of the 15th annual European conference on Algorithms
Orientation-based models for {0,1,2}-survivable network design: theory and practice
Mathematical Programming: Series A and B - Series B - Special Issue: Combinatorial Optimization and Integer Programming
Local search genetic algorithm for optimal design of reliablenetworks
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
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This paper presents a biobjective genetic algorithm (GA) to design reliable two-node connected telecommunication networks. Because the exact calculation of the reliability of a network is NP-hard, network designers have been reluctant to use network reliability as a design criterion; however, it is clearly an important aspect. Herein, three methods of reliability assessment are developed: an exact reliability calculation method using factoring, an efficient Monte Carlo estimation procedure using the sequential construction technique and network reductions, and an upper bound for the all-terminal reliability of networks with arbitrary arc reliabilities. These three methods of reliability assessment are used collectively in a biobjective GA with specialized mutation operators that perturb solutions without disturbing two-node connectivity. Computational experiments show that the proposed approach is tractable and significantly improves upon the results found by single-objective heuristics.