Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
Topological design of local-area networks using genetic algorithms
IEEE/ACM Transactions on Networking (TON)
Bicriteria network design problems
Journal of Algorithms
Introduction to algorithms
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Multi-Objective Optimization: Performance Assessments and Comparisons
Artificial Intelligence Review
Combining convergence and diversity in evolutionary multiobjective optimization
Evolutionary Computation
Computing a Diameter-Constrained Minimum Spanning Tree in Parallel
CIAC '00 Proceedings of the 4th Italian Conference on Algorithms and Complexity
Proceedings of the 2003 ACM symposium on Applied computing
A novel hybrid immune algorithm for global optimization in design and manufacturing
Robotics and Computer-Integrated Manufacturing
A new design optimization framework based on immune algorithm and Taguchi's method
Computers in Industry
Edge sets: an effective evolutionary coding of spanning trees
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
Topological design of interconnected LAN/MAN networks
IEEE Journal on Selected Areas in Communications
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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Abstract: Multiobjective network design is known to be a notoriously hard problem. Unfortunately, the problem has several practical applications such as multicast communication and VLSI design. Most network topology design problems involve simultaneously optimizing multiple conflicting objectives such as average delay and network equipment cost while satisfying flow and reliability constraints. In this paper, we formalize a network design problem and present randomized and deterministic heuristics to solve the problem. We first present a multi-objective evolutionary algorithm which obtains a diverse set of near-optimal solutions. We also design a multiobjective deterministic heuristic based on branch exchange. We test our algorithms on Poisson and Self-similar traffic models using data collected from real networks. We empirically show that our heuristics perform well across networks of various sizes.