Multicast routing for multimedia communication
IEEE/ACM Transactions on Networking (TON)
Topological design of local-area networks using genetic algorithms
IEEE/ACM Transactions on Networking (TON)
Approximation algorithms for NP-hard problems
Approximation algorithms for NP-hard problems
Bicriteria network design problems
Journal of Algorithms
SAC '94 Proceedings of the 1994 ACM symposium on Applied computing
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Combining convergence and diversity in evolutionary multiobjective optimization
Evolutionary Computation
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
Evolutionary Computation
Local search genetic algorithm for optimal design of reliablenetworks
IEEE Transactions on Evolutionary Computation
An integrated system for designing minimum cost survivable telecommunications networks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An edge-based heuristic for Steiner routing
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Analysis of a multiobjective evolutionary algorithm on the 0-1 knapsack problem
Theoretical Computer Science
Multiobjective network design for realistic traffic models
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Running time analysis of a multiobjective evolutionary algorithm on simple and hard problems
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
Proceedings of the 45th Annual Simulation Symposium
Network topology planning using MOEA/D with objective-guided operators
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
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In this paper, we revisit a general class of multicriteria multi-constrained network design problems and attempt to solve, in a novel way, with Evolutionary Algorithms (EAs). A major challenge to solving such problems is to capture possibly all the (representative) equivalent and diverse solutions. In this work, we formulate, without loss of generality, a bi-criteria bi- constrained communication network topological design problem. Two of the primary objectives to be optimized are network delay and cost subject to satisfaction of reliability and flowconstraints. This is a NP-hard problem so we use a hybrid approach (for initialization of the population) along with EA. Furthermore, the twoobjective optimal solution front is not known a priori. Therefore, we use a multiobjective EA which produces diverse solution space and monitors convergence; the EA has been demonstrated to work effectively across complex problems of unknown nature. We tested this approach for designing networks of different sizes and found that the approach scales well with larger networks. Results thus obtained are compared with those obtained by two traditional approaches namely, the exhaustive search and branch exchange heuristics.